Staff GenAI Research Scientist - Retrieval

P-1214

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform, so our customers can focus on the high value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and systems using their own data, with technologies ranging from pre-training LLMs from scratch to augmented generation using the latest retrieval techniques. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models are just as valuable as any other core IP, and that high-quality AI models should be available to all.

Job Description 

As a Staff Research Scientist on the Enterprise Agents team, you will be responsible for keeping up with the latest developments in Agent Context, Information Retrieval, Knowledge Assistants, RAG, Embeddings, and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Staff Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on Information Retrieval for reusable Agent components, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches.
• Drive research and technical strategy across enterprise retrieval and search, including workspace search, vector search.
• Drive algorithmic innovations for Retrieval within Large Language Models. 
• Experience with Agent Benchmarks for retrieval, text-embeddings and LLM Data Quality. 

What We Look for

• 5+ years of 
• PhD in Computer Science or related field with strong foundations in Natural Language Processing and Information Retrieval 
• Developing and implementing methods that extend and improve model capabilities, reliability, and safety. 
• Strong preference for candidates with first-author publications at top ML/systems conferences (EMNLP, ICLR, ACL, NeurIPs) focused on optimization or efficiency.

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description 

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will: 

• Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
• Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
• Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for

• MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
• Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
• Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.

We are looking for a Senior Software Engineer specializing in Machine Learning to join our Revenue ML team at Discord. This team partners with our revenue product groups, focusing on both consumer revenue and our emerging Ads initiative. This role will specifically contribute to our Ads ML efforts, helping to build and scale ML capabilities in areas such as ads measurement, targeting, and delivery ranking.

As part of this team, you will play a critical role in developing foundational ML models that enhance ad relevance, optimize performance, and drive revenue. This is a unique opportunity to work on an early-stage Ads ML platform and have a direct impact on the business's success. Our tech stack includes Python, ML frameworks like PyTorch and TensorFlow, large-scale data infrastructure, and real-time ad-serving technologies.

What You'll Be Doing:

• Design, develop, and deploy machine learning models for ads targeting and ranking.
• Develop sophisticated ML solutions such as identity graph to enhance ad targeting.
• Build and optimize ad ranking models to serve the most effective ads based on campaign objectives (e.g., app installs, link click).
• Improve ads targeting and ranking by leveraging both on-platform and off-platform signals.
• Collaborate cross-functionally with product, engineering, and business teams to define and execute on the Ads ML roadmap.
• Scale our ML infrastructure to support an increasing number of concurrent ad campaigns while ensuring low-latency decision-making.
• Drive research and implementation of state-of-the-art ML techniques in the field of online advertising.

What You Should Have:

• 5+ years of experience as a Machine Learning Engineer or Data Scientist.
• 3+ years of experience specifically in Ads ML (ads ranking, personalization, optimization, privacy-compliant user modeling, targeting, or measurement).
• Strong proficiency in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
• Experience with applied deep learning (e.g transformers, embedding models).
• Proven track record of designing, implementing, and scaling ML-driven ad systems in real-world applications.
• Experience working with real-time ML inference, A/B testing, and optimization frameworks.
• Experience translating ML evaluation results and performance metrics into actionable product roadmap items.
• Ability to connect business objectives to ML solutions, with the flexibility to shift focus toward the highest-impact problems as priorities evolve.

Bonus Skills:

• Strong understanding of performance advertising and how ML impacts revenue and advertiser retention.
• Knowledge of ad tech industry standards and ads ecosystem including targeting, retrieval, ranking, pacing, frequency, auction, etc.
• Experience with large-scale recommendation systems.
• Experience with large-scale data infrastructure and distributed computing

The US base salary range for this full-time position is $220,000 to $247,000 + equity + benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

About the role

As part of our growing Data Science and Analytics team, you will play an instrumental role in our company’s mission of building safe and beneficial artificial intelligence by driving data-informed decision making across our organization. You’ve worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale. In this unique company, technology, and moment in history, your work will be critical to informing our strategy as we deploy safe, frontier AI at scale to the world.

Responsibilities:

• Define core metrics, build measurement frameworks, and maintain core reporting to evaluate success
• Deep dive into product and user data to derive actionable insights and size opportunities to improve products, strategy and operations, influencing roadmaps through your insights and recommendations
• Develop hypotheses, apply rigorous causal inference methods – controlled experiments, synthetic controls –  and analyze the results in order make actionable recommendations 
• Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
• Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
• Present complex technical analyses and recommendations to both technical and non-technical stakeholders
• Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration and decision-making as our products grow

You may be a good fit if you have:

• 7+ years of experience in data science or analytics roles 
• Deep expertise with Python, SQL, and data visualization tools
• Expertise with experimental design, causal inference, statistical modeling, and A/B testing frameworks, particularly in high-scale technical environments
• Highly effective written communication and presentation skills
• A track record of translating complex data into clear, actionable insights for both technical and business stakeholders
• A bias for action and ability to thrive in ambiguous, fast-moving environments where you must create clarity and drive forward progress
• A passion for the company’s mission of building helpful, honest, and harmless AI
• Some experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem

We’re hiring across multiple pillars

Applying for this role will allow you to be considered for all pillars currently hiring. You will be asked to select a preference when submitting an application.

Claude Code

This role is embedded with the Claude Code product team, driving data-informed decisions for Anthropic's agentic coding tool that enables developers to delegate coding tasks directly to Claude from their terminal. You'll help the team understand how developers interact with AI coding assistants, measure developer productivity and product quality, and identify opportunities to innovate the developer experience as the product scales. Key focus areas include developer usage patterns across the platform, driving adoption within the developer ecosystem, and developer segmentation.

Strong candidates may have:

• Deep familiarity with software development workflows, developer tools, and engineering productivity metrics—ideally from working at developer-focused companies or on products targeting software engineers
• Experience analyzing human-AI interaction patterns, particularly in code generation or developer tooling contexts
• Experience supporting product teams building for the Enterprise

Consumer Data Scientist

You will be embedded with our Consumer product team. This team is responsible for building all consumer-facing Claude experiences—including web, mobile, desktop, and browser extensions. In this role, you'll shape how millions of users interact with Claude daily, driving product insights to product recommendations for interfaces that are intuitive, responsive, and push the boundaries of what AI-powered applications can be.

Strong candidates may have:

• Experience working closely with Product and Engineering teams on consumer products across multiple platforms (web, iOS, Android, desktop, browser extensions)
• Demonstrated impact on product roadmap and strategy from data deep dives in consumer growth, engagement and retention
• Expert in experimentation, holding a high statistical bar for measuring the impact of core product changes

Platform Product Data Scientist

You will partner closely with product, engineering, and go-to-market teams to understand how developers and enterprise customers build on and adopt the Claude Developer Platform—spanning our core API, agent orchestration, tool and MCP integrations, and knowledge management capabilities. You'll identify growth opportunities, surface insights about how AI agents are being built and deployed at scale, and drive data-informed decisions that shape our platform roadmap.

Strong candidates may have:

• 3+ years of experience working closely with Product or Engineering teams on API or developer-facing products, with demonstrated impact on product roadmap and strategy
• Experience supporting B2B sales teams with data insights
• Strong instincts for what drives product adoption, engagement, and retention

Model Experience Data Scientist

You will work closely with product, engineering, and research leaders to bring data-driven rigor to every phase of model development and launch. Sitting at the true bleeding edge of putting frontier AI research into the public domain, you will leverage data from both external customers and internal testing to define and measure key company success metrics, and analyze user and model behavior to identify new opportunities to push the frontier. 

Strong candidates may have:

• 3+ years of experience deeply embedding in Product or Research teams, preferably working with LLM or AI products
• Comfort working with unstructured data

About the role

Anthropic is compute-constrained, and how we allocate that compute is one of the highest-leverage decisions we make as a company. Today, those allocation choices are only loosely tied to the user outcomes we ultimately care about — retention, lifetime value, and the experience of people relying on Claude. You will change that.

As a hands-on technical IC on the Supply pillar of our Data Science & Analytics team, you'll sit alongside the infrastructure engineers who run our compute and help decide how our scarcest resource gets used. You'll design and run the analyses, observational and synthetic experiments, and optimization frameworks that turn opaque supply decisions into shared, measurable understanding across the company. Your work will directly shape how frontier AI reaches the world at scale, and your findings will go in front of senior leadership, including our CTO and his staff.

This role is a fit for someone who thinks natively in terms of constrained allocation and queueing, who enjoys getting close to the system rather than analyzing it from a distance, and who wants their analyses to translate into operational changes that ship.

Responsibilities:

• Build and run testing frameworks — observational and synthetic — to quantify how different inputs affect compute allocation outcomes
• Connect compute allocation decisions to downstream user outcomes (retention, LTV, revenue) so we stop optimizing in a vacuum
• Partner closely with infrastructure engineers, product, and research to instrument the system, measure what matters, and ship operational changes
• Develop the metric hierarchies, dashboards, and reporting that turn supply decisions into shared understanding across the company
• Contribute analyses and recommendations to executive forums, and co-author the supply narrative the team takes to the CTO and his staff
• Measure and improve how AI affects developer productivity inside Anthropic

You may be a good fit if you have:

• Strong technical IC background in data science, analytics, or operations research
• Operations research foundation — you think natively in terms of optimization, constrained allocation, and queueing
• Deep proficiency with Python, SQL, and data visualization tools
• Track record of owning analyses end-to-end and communicating results clearly to engineering and product leadership
• Direct experience working closely with engineering teams on production systems
• A passion for Anthropic's mission of building helpful, honest, and harmless AI

Strong candidates may have:

• 5+ years of technical IC experience in data science, analytics, or operations research; 8+ years for candidates targeting a Staff-level scope
• Experience with highly complex systems with many interacting components (ad networks, payment processing, marketplace matching, routing, etc.)
• Experience with causal inference methods applied to operational decisions (synthetic controls, geo-experiments, switchbacks)
• Experience contributing to or designing experimentation platforms, not just using them
• Exposure to AI/ML products, large language models, or large-scale inference systems
• Track record of setting technical direction across multiple workstreams or mentoring senior ICs without formal management responsibility

Deadline to apply: None. Applications are accepted on a rolling basis.

We are seeking a high-impact Staff Data Scientist to play a leading role on our data needs to bridge the gap between advanced research and production-grade ML systems. You will be a key technical leader and partner to our Research Scientists, driving the evolution of our AI algorithms through rigorous data science methodologies, strategic data curation, and cross-functional leadership.

Job Responsibilities:

• Vision & Cross-Functional Leadership: Engage with cross-functional teams (Product, Research, Engineering, and Process Engineering) and help guide the overarching vision for data analysis, curation, and annotation to improve our AI models. Drive the definition of algorithm and data requirements necessary to deliver on end-point objectives.
• Data Campaigns and Annotation Strategy: Introduce best practices and efficient processes to enable multiple, large-scale annotation campaigns for continuous AI product improvements. Spearhead the strategic design of data campaigns needed to advance AI algorithms.
• Advanced Data Curation & Management: Develop comprehensive data curation strategies for improvements to AI models. Partner with MLOps to architect data management systems for algorithm training and performance validation, and establish data dashboards and monitoring reports.
• Performance Evaluation and Statistical Analysis: Establish frameworks and develop tools to rigorously evaluate the strengths and weaknesses of model iterations across patient populations. Design and oversee data analyses using statistical techniques to illuminate the performance of our AI algorithms.

Required Qualifications:  

• Education: Masters or PhD Degree in Engineering, Computer Science, Statistics, Data Science or related degree.
• Work Experience: 7+ years (or 5+ with PhD) of proven track record in Data Science, Machine Learning, Computer Vision, or Image Analysis in industry. Have a wealth of experience from working on complex, real-world AI problems in medical imaging or computer vision requiring careful consideration of data needs.
• Software: Proficient in Python, including statistical and machine learning packages (e.g. scipy, sklearn, statsmodels, seaborn) with a commitment to writing clean, reproducible and scalable code. Familiarity with image and 3D processing tools like VTK and ITK, and visualization tools like 3DSlicer and MITK, a plus.
• Statistics: Understanding of standard statistical techniques and ability to apply appropriate statistical methods to a range of data structures; experience with medical imaging data a plus.
• Data Management: Experience working with data lakes, SQL/No SQL Databases, AWS Cloud Storage, Tableau dashboards.
• AI & Medical Imaging: Expertise in deep learning and machine learning models in production. Strong experience working with medical imaging data (CT and vascular imaging) is highly preferred.
• (Preferred) Proficiency in Agentic AI Tools: Experience integrating generative AI and agentic tools into daily workflows to act as a force multiplier—accelerating coding, prototyping, and complex data analysis—while demonstrating the critical judgment required to rigorously evaluate AI outputs for accuracy.
• Communication: Excellent written and verbal communication. Detail orientated but able to describe complex topics in a manner that is digestible to a broad audience. Ability to distill complex analyses into interpretable and actionable findings.
• Commitment: Committed to the success of the team and successful completion of project - 75% confidence / 100% committed.
• Influence without Authority: Able to build trust and obtain cross-functional alignment across departments.

A reasonable estimate of the base salary compensation range is $220,000 to $280,000, bonus, and equity. #LI-IB1 #LI-Hybrid

• Develop multimodal foundation models spanning image and molecular data
• Design approaches that unify representation learning and generative modeling
• Train large-scale models on structured, high-dimensional datasets
• Explore cross-modal alignment, prediction, and generation
• Build scalable systems for data processing, training, and evaluation
• Work in a research-driven environment with evolving problem definitions

• Experience with representation learning (self-supervised, contrastive, masked modeling, etc.)
• Experience with generative modeling (diffusion, autoregressive models, VAEs, or related approaches)
• Proficiency in Python, ML frameworks, and CI/CD (PyTorch, JAX, etc.)

• Work on multimodal learning or cross-domain representation learning
• Experience with image data, molecular / omics-like data, or both
• Familiarity with large-scale training

• Exposure to biological or scientific datasets
• Experience with paired or partially aligned multimodal data
• Comfortable working in open-ended, evolving problem spaces

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $170,000 - $240,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
Xaira Therapeutics is seeking a lab-based Senior Scientist in Inflammation and Immunology to join our Biology & Pharmacology department. This role is ideal for someone who thrives in a hands-on research environment, has experience working with primary human or mouse immune cells and ex vivo tissue systems, and is excited to help shape therapeutic program strategy.

In this role, you will investigate disease biology and drug mechanisms, generate actionable data, and contribute to advancing therapeutic programs through cross-functional collaboration.

What You’ll Do

• Drive preclinical programs by designing and executing in vitro and in vivo studies that explore disease biology, target validation, and lead candidate development.
• Identify knowledge gaps, ask critical mechanistic questions to guide program direction, and evaluate novel targets and therapeutic strategies.
• Dissociate human tissue biopsies into single-cell suspensions or establish human tissue slice cultures for downstream functional or phenotyping assays.
• Lead immune profiling and functional characterization using high-parameter flow cytometry (15+ colors or spectral platforms), functional assays (T cell activation, differentiation, proliferation, suppression), and molecular/cytokine profiling (MSD, Luminex, qPCR, RNA sequencing).
• Translate experimental data into actionable insights and clearly communicate findings and recommendations to cross-functional teams.

What We’re Looking For

• PhD in Immunology or a related field with 3+ years of relevant experience; industry experience preferred.
• Track record of impact through publications, presentations, or applied research.
• Hands-on experience with primary human or mouse immune cells and/or ex vivo tissue systems.
• Strong expertise in flow cytometry, including high-parameter panel design, execution, and data analysis.
• Proven ability to independently plan, execute, troubleshoot, and interpret experiments.
• Highly organized, with the ability to manage multiple workstreams in a fast-paced environment.
• Clear communicator who can distill complex data into actionable insights.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $140,000 - $170,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role
As a Senior Research Associate Scientist in the Protein Engineering group, you will be a crucial member of our interdisciplinary team, comprising highly creative and talented individuals with exceptional expertise in protein characterization and engineering. This group is responsible for enabling AI drug discovery efforts and optimizing lead molecules. You will work collaboratively with protein designers, biologists, and other drug discovery team members.

We’re looking for an extraordinary library builder who can design, generate and scale complex DNA assemblies for our protein engineering and display teams. This role requires extensive experience with combinatorial, designed and naive library building with the relevant microbiological and protein level expertise to express & qualify them once built. This hands-on role is best for someone who can keep NGS, protein biochemistry, and DNA assembly needs in mind when building complex libraries at speed. 

About You
You are an enthusiastic protein biochemist who takes pride in your bench execution skills. Your passion lies in display technology, drug discovery and developing novel treatments for patients. You are conscientious, detail-oriented, and organized. Collaboration comes naturally to you, and you thrive in a fast-paced environment where pushing the boundaries of what is possible is the norm.

What You'll Do and Learn

• Design and apply multiple innovative selection techniques utilizing synthetic libraries, like phage, yeast display, and mammalian display. 
• Utilize FACS sorting, plate-based screening, and NGS to identify binders.
• Setup and use automation to further rank leads for affinity and function. 
• Collaborate with cross-functional teams to troubleshoot protein reagents. 
• Train and mentor junior team members, providing guidance on experimental design, data analysis, and troubleshooting.
• Maintain accurate and detailed records of experiments, protocols, and results in accordance with company standards and regulatory requirements.
• Interpret and present scientific findings at research meetings. Provide scientific input and propose follow-up experiments.
• Collaborate and communicate across diverse research teams to successfully achieve scientific goals.
• Contribute to scientific publications, patents, and presentations to disseminate research findings both internally and externally.

Qualifications

• Bachelor of science or master degree in Molecular Biology, Protein Biochemistry, or related fields with 5+ years of industrial experience.
• Hands-on experience with yeast display system and library building.
• Cloning complex assemblies with multi-part golden gate, gibson, and other techniques
• Experience with DNA synthesis CROs.
• High proficiency in yeast display to protein targets, soluble and membrane.
• Proficiency in molecular and cell biology techniques, such as DNA extraction, PCR, enzymatic DNA treatments and library preparation QC for NGS..
• Mammalian tissue culture.
• Antibody engineering and discovery experience.
• Flow cytometry experience (both analytical and sorting). 
• Excellent analytical and problem-solving skills, with meticulous attention to detail.
• Strong written and verbal communication skills, with the ability to effectively present complex scientific concepts to both technical and non-technical audiences.
• Ability to work effectively in a collaborative, multidisciplinary team environment, fostering cooperation and knowledge-sharing among team members.
• Experience using LIMS and Benchling systems.

Nice to have Skill(s)

• Experience in protein purification techniques (including affinity, ion exchange, HIC, SEC) and in chromatography hardware and software (Cytiva AKTA, Agilent HPLC).
  
  

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $110,000 - $138,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role

We are seeking a driven Scientist and experimentalist who combines strong hands-on molecular biology skills with a creative, critical, and builder-oriented mindset. This role is focused on assisting in the design, construction, and iteration of novel screening platforms and experimental workflows that enable biological discovery at scale.

The ideal candidate is a self-starter who enjoys working in ambiguous problem spaces, thinks deeply about experimental design, and takes ownership of turning early ideas into robust, reproducible systems. You will work collaboratively with other teams, including automation, engineering, and computation, to invent new ways of generating high-quality biological data.

Key Responsibilities

• Develop novel antibody screening technologies and experimental platforms, from early proof-of-concept through scalable, robust workflows
• Design, implement, and optimize screening assays, including biochemical, molecular, and cell-based readouts
• Assist multidisciplinary platform development efforts as a biochemical expert through microbial and mammalian cell line engineering (e.g. cloning, genome editing, expression optimization)
• Apply data-driven and critical thinking approaches to troubleshoot, refine, and improve workflows, enhancing throughput, robustness, and interpretability
• Clearly document experimental workflows, present results, and contribute to shared platform standards while maintaining flexibility for rapid exploration
• Collaborate closely with cross-functional partners (automation, engineering, computation) to integrate biology, data, and technology into cohesive systems

Required Qualifications

• PhD in Molecular Biology, Bioengineering, Biochemistry, or a related field with 1+ years of industry experience, or
  B.S. or M.S. with 8-10 years of relevant industry or applied research experience
• Prior work on platform, workflow, or method development, especially in exploratory or early-stage settings (see examples under Bonus Skills)
• Experience with antibody discovery and engineering workflows, including panning, enrichment, or display-based screening approaches
• Experience with assay development, optimization, and experimental troubleshooting
• Strong hands-on experience in molecular cloning and DNA manipulation
• Experience with cell-line engineering (e.g. E. coli, yeast, mammalian or related systems)
• Demonstrated ability to work independently, think critically, and drive conclusive experiments
• Strong organizational skills and attention to experimental detail

Preferred Qualifications

• Experience with functional antibody screening or protein–protein interaction assays
• Familiarity with high-throughput or semi-automated screening systems
• Experience working with data-rich experimental systems
• Comfort operating in fast-moving, collaborative, and partially undefined problem spaces

Nice to Have

Experience in one or more of the following areas would be a plus:

• Spatial biology technologies (e.g. spatial transcriptomics, in situ or imaging-based assays)
• Single-cell technologies, including single-cell sequencing or high-content single-cell assays
• Microarray-based assays or other multiplexed screening formats
• Microfluidics, particularly for screening, assay miniaturization, or single-cell applications
• High-content imaging or phenotypic screening
• Experience studying or manipulating cell-internal signaling pathways (e.g. receptor signaling, transcriptional regulation, immune signaling, stress responses, or related pathways)
• Protein expression, secretion, or trafficking assays

Compensation: Annual

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity.  The base pay range for this position is expected to be $110,000 - $138,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

About the Role

You are an enthusiastic protein biochemist who takes pride in your bench execution skills. Your passion lies in display technology, drug discovery and developing novel treatments for patients. You are conscientious, detail-oriented, and organized. Collaboration comes naturally to you, and you thrive in a fast-paced environment where pushing the boundaries of what is possible is the norm.

Responsibilities

• Build, adapt, and automate display systems to facilitate AI antibody design. 
• Establish, develop, and/or optimize cutting edge technologies to enable data generation at scale for AI model training or evaluation
• Design and apply multiple innovative selection techniques to provide data at scale based on ML training needs. 
• Design, setup, optimize, and use automation to characterize affinity and function at the clonal level. 
• Contribute to the preparation of technical reports and presentations.
  
  

Qualifications

• Significant hands-on experience with protein display techniques such as yeast and/or phage display. Experience in library design, build, panning/sorting and validation. 
• Bachelor of Science or Master’s degree in Molecular Biology, Biology, Biochemistry, or related fields with 2-6 years of industrial experience.  . 
• Familiarity with antibody binding assays and automating them (ELISA, SPR, FACS).
• Proficiency in molecular and cell biology techniques, including mammalian tissue cell culture, and basic skills in molecular biology labs.
• Working knowledge of software and programming for large data set analysis.
• Excellent analytical and problem-solving skills, with meticulous attention to detail.
• Strong written and verbal communication skills, with the ability to effectively present complex scientific concepts to both technical and non-technical audiences.
• Ability to work effectively in a collaborative, multidisciplinary team environment, fostering cooperation and knowledge-sharing among team members

Schedule Flexibility: Due to the nature of experimental workflows, this role will require availability on weekends (approximately every couple of weeks). 

Employment Type: Contract

Contract Duration: 9 Months

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $45-$60 hourly; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.

Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

Location: San Francisco, CA (Hybrid) 

What is Verse? 

Energy markets are more volatile than ever. Rapid electrification and the rise of AI are driving unprecedented demand for power, while energy costs continue to rise across the globe. For the world’s largest energy buyers, managing energy has never been more complex or more critical.

Verse helps these organizations manage complex power portfolios with confidence by unifying energy data, planning, forecasting, and operations in one tool. Our Energy Cost Intelligence platform, Aria, brings together energy, finance, and operations teams with real-time, finance-ready intelligence—replacing spreadsheets and consultants with precision across the entire energy lifecycle. Built by an expert team of energy buyers, data scientists, and engineers, Verse enables faster, smarter energy decisions that reduce risk and lower energy costs.

The Role

Verse is seeking a Data Scientist to join our Data Science Team. In this role, you will lead the development and deployment of advanced data-driven solutions across a range of applications, including electricity markets, renewable procurement, and energy risk management. You will shape the machine learning and data modeling foundations that Verse's software is built on. For example, you might spend a cycle deploying electricity market price forecasting pipelines for new regions, developing solar production anomaly detection models, or creating scalable tools for benchmarking energy project financial performance.

Key Responsibilities

• Lead End-to-End Data Science Projects: Own and drive projects from problem definition through scoping, modeling, validation, and production deployment. Translate business problems into scalable, high-impact modeling solutions.
• Statistical & Machine Learning Modeling: Design, develop, and refine statistical and machine learning models (e.g., time series forecasting, probabilistic models) to support decision-making and enhance product capabilities.
• Analytics Engineering & Data Modeling: Perform complex data transformations and develop well-structured data models. Translate business and analytical requirements into scalable, tested, and well-documented datasets.
• Software Development & Productionization: Write clean, efficient, and maintainable Python code. Contribute to integrating models into production systems in a cloud-based environment while leveraging AI coding tools to accelerate development.
• MLOps: Contribute to Verse’s machine learning modeling infrastructure to support scaling of ML models and improving reliability, monitoring, and performance in production.
• Cross-Functional Collaboration: Partner with product, engineering, and business stakeholders to ensure models and insights are aligned with user needs and effectively integrated into workflows.

What We're Looking For (Minimum Qualifications)

• Master’s degree in Computer Science, Statistics, Engineering, Applied Mathematics, or a related quantitative field and 2+ years of professional experience in data science or machine learning; or
• Bachelor’s degree and 4+ years of professional experience in data science or machine learning
• Strong foundation in statistical modeling and machine learning, including time series forecasting and model evaluation
• Experience deploying and maintaining models in cloud-based environments (e.g., AWS, GCP, or Azure) using MLOps practices
• Strong Python expertise, including experience with scientific computing and ML libraries (e.g., NumPy, pandas, scikit-learn, PyTorch, TensorFlow)
• Hands-on experience in orchestrating complex data transformations (e.g. Airflow, Dagster, dbt)
• Strong software engineering practices (version control, testing, code reviews, CI/CD)
• Strong communication skills, with the ability to explain technical concepts to non-technical stakeholders

What Will Make You Standout (Preferred Qualifications)

• Experience in energy, climate tech, or related domains (not required)
• Familiarity with optimization methods or operations research
• Experience developing probabilistic forecasting models and quantifying uncertainty
• PhD in a quantitative field

What Makes Verse a Great Place to Work? 

• Lead with Empathy: We lift each other up with humility and kindness, always putting colleagues and customers first
• Be Honest & Transparent: We prioritize effective communication to build trust with our team, customers, and stakeholders
• Move with Balance & Precision: We believe speed and perseverance must be accompanied by thoughtfulness and reflection
• Leave the World a Better Place: We are passionate about our mission, and we strive to create a sustainable world for future generations

Base Pay Range

$146,000 - $172,000

This is the estimated base salary range for this position, which does not include the value of benefits or a potential equity grant. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.

Benefits and Employee Perks 

• Competitive compensation and equity grant at a high-growth start up 
• Comprehensive benefits package including medical, dental and vision insurance, and 401k 
• Flexible hours and unlimited PTO 
• Diverse and inclusive working environment 

Verse is an equal opportunity employer. All applicants and employees are considered for hire, promotion, and compensation without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, marital or familial status.

Verana Health, a digital health company that delivers quality drug lifecycle and medical practice insights from an exclusive real-world data network, recently secured a $150 million Series E led by Johnson & Johnson Innovation – JJDC, Inc. (JJDC) and Novo Growth, the growth-stage investment arm of Novo Holdings. 

Existing Verana Health investors GV (formerly Google Ventures), Casdin Capital, and Brook Byers also joined the round, as well as notable new investors, including the Merck Global Health Innovation Fund, THVC, and Breyer Capital.

We are driven to create quality real-world data in ophthalmology, neurology, urology, and oncology to accelerate quality insights across the drug lifecycle and within medical practices. Additionally, we are driven to advance the quality of care and quality of life for patients. DRIVE defines our internal purpose and is the galvanizing force that helps ground us in a shared corporate culture. DRIVE is: Diversity, Responsibility, Integrity, Voice-of-Customer and End-Results. Click here to read more about our culture and values.

Our headquarters are located in San Francisco and we have additional offices in Knoxville, TN and New York City with employees working remotely in AZ, CA, CO, CT, FL, GA, IL, LA, MA, MN, NC, NJ, NV, NY, OH, PA, SC, TN, TX, VA, WA, D.C. All employees are required to have permanent residency in one of these states. Candidates who are willing to relocate are also encouraged to apply. 

Candidates based in the Bay Area, New York City, and Knoxville, Tennessee will be give priority consideration. For these locations, the position will follow a hybrid work model, with 3 days per week in office and the remaining days working from home. 

*Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over sponsorship of an employment Visa at this time.*

Job Title: Quantitative Scientist

Why This Role Matters:

The Quantitative Scientist will be responsible for executing and providing oversight and guidance on the analytical, statistical and epidemiological components of Verana research projects and data quality initiatives. The primary function of this role will be to conduct, guide, and manage the analytical execution of Verana research projects . The Quantitative Scientist will collaborate cross-functionally to build research capacity and adopt quality standards across Verana's business units.  This position requires an experienced individual with knowledge of statistics, ability to develop and review code with a solid understanding of coding best practices, a strong understanding of epidemiological study designs, as well as excellent communication and interpersonal skills.  In addition, you should be able to continually unearth and present interesting trends that have clinical, research, and business importance for our customers and oncology patients at large.  You will be joining a friendly, high performing and diverse research team with backgrounds in public health, health economics, biology, and statistics.  This role will report to the Vice President, Research.

WHAT WILL YOU GAIN

• Expertise in the oncology real-world data industry, a fast-growing segment of health data
• Experience executing oncology research and analytical/statistical methods to answer key questions for patients, providers, and life science companies

WHAT TO EXPECT IN YOUR FIRST YEAR AT VERANA:

In thirty days, you will:

• Understand the full suite of Verana’s research offerings and analyses
• Understand the research team’s GitHub repo and analysis template 

In three months, you will:

• Contribute to internal and external meetings related to Verana research and analyses
• Gain expert understanding of Verana’s data model  
• Implement clinical specifications on real-world data and add to the suite of functions available for analyses

In six months, you will:

• Personally execute analytical research projects
• Contribute to the development of project collateral, research protocols, abstracts, posters and manuscripts
• Guide and mentor data scientists and analysts 

In one year, you will:

• Lead the analytical execution of Verana’s research projects for life science, provider, and regulatory partners 
• Scope projects to determine feasibility, estimated costs, and expected timelines
• Provide guidance to Verana’s client partners in the use of Verana’s data model and analytical/statistical methodologies 

HOW YOU WILL IMPACT VERANA

• Lead the design and development of Verana research studies from a statistical and analytical perspective
• Contribute to the development of protocols and statistical analysis plans 
• Develop code and produce results as defined in protocols and statistical analysis plans
• Collaborate with physicians, statisticians, data scientists, business leaders, and others within and outside Verana to conduct research projects including observational studies, pharmacoeconomic analyses, and other relevant study types
• In partnership with the Research Team, communicate studies in progress and demonstrate results to key stakeholders through high quality abstracts, posters, and publications
• Manage and mentor a team of data analysts and data scientists, including reviewing code and analytical output
• Contribute to the evolution of Verana’s quality assurance framework, including identifying data quality issues during analysis
• Maintain current and in-depth understanding of real-world data analytical methodologies, along with the ability to lead and mentor internal team members in successfully executing them

WHAT YOU BRING TO THE TABLE

• Masters degree in computer science, statistics, applied math, econometrics, MPH, or similar quantitative field
• 3+ years of relevant research experience in the field of oncology (post-graduation)
• Experience working with real-world data sourced from electronic health records
• Experience analyzing claims data 
• Advanced knowledge of SQL, R programming, and version control (git)
• Deep understanding and experience with descriptive statistics, logistic and multivariate regression analysis, power calculations, propensity score analysis, and survival analysis
• Significant experience developing protocol documents, statistical analysis plans (SAPs), and manuscript tables and figures
• Evidences well-developed conceptual and integrative thinking with ability to access internal and external resources as needed 
• Project implementation and execution, including engagement with key stakeholders, with a high degree of autonomy
• Mentors junior analysts in HEOR and statistical analysis methodologies
• Excellent written and verbal communication skills
• Strong organizational and time management skills 
• Works well independently, as a team member, and as a team leader 
• Comfort working in a fast-paced, dynamic environment

NICE TO HAVE

• Experience implementing data science methodologies
• Understanding of data quality metrics and/or quality management systems

Benefits:

• We provide 100% health, vision, and dental coverage for employees 
• 401K Match
• Flexible vacation plans 
• $700 learning and wellness annual stipend 
• Headspace meditation app access

Final note:

You do not need to match every listed expectation to apply for this position. Here at Verana, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.

Caution to Job Applicants: Be vigilant against potential scams. Verana Health will never ask for payment or personal information upfront. Verify company details, cross-check job offers, and trust your instincts. Any legitimate job offer will be received by a Verana Health email account (not via gmail, text or other means) Report suspicious activities to protect yourself and others in the job-seeking community.

#LI-REMOTE

About the Role
Our Data Science team is a world-class data, applied science, and ML organization that leads data-driven decision-making and the conversational AI efforts for the entire company. Joining our team offers a high-growth career opportunity to work with some of the world’s most talented data scientists in a high-performance and high-impact culture.

What You’ll Accomplish

• Lead the development of statistical, econometric, optimization, and machine learning models for a range of applications in our messaging and AI product offerings
• Design and execute experiments, interpret results, and draw actionable conclusions
• Use data to understand product performance, identify improvement opportunities, and define product/team roadmaps
• Present findings to senior leadership to inform and influence business decisions
• Collaborate with cross-functional teams across product, engineering, client services, and sales to drive business value from ideation to production

Your Expertise

• Ph.D., M.S. or Bachelors degree in Statistics, Economics, Machine Learning, Operations Research, or other quantitative fields
• Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, economics, and analytics
• Knowledge of experimental design and analysis
• Experience with exploratory data analysis, statistical analysis and testing, and model development
• Ability to use Python to work efficiently at scale with large data sets
• Advanced proficiency in SQL

Nice to Haves

• 4+ years of industry experience as an Applied or Data Scientist or equivalent
• Familiarity with advanced statistical inference, experimentation, and causal inference methods
• Econometric experience with pricing and promotion optimization
• Expertise in customer lifetime value modeling
• Experience in personalization systems and cross-sectional cohort modeling
• Background in operations research (e.g., scheduling or assignment problems)
• Knowledge of advanced topics in XGBoost modeling

You'll get competitive perks and benefits, from health & wellness to equity, to help you bring your best self to work.

For US based applicants:

• The US base salary range for this full-time position is $250,000 - $300,000 annually + equity + benefits
• Our salary ranges are determined by role, level and location

#LI-MDK1

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Description

Reporting to the SVP of Research, the Senior Scientist I, Medicinal Chemistry will bring deep expertise in medicinal chemistry and will play a key role in advancing a pipeline of novel therapeutics enabled by integrin biology and targeted delivery strategies. This role will lead the design and optimization of drug candidates that leverage integrin-mediated delivery to selectively target tissues and cell types.

Responsibilities

• Design and drive medicinal chemistry strategies for integrin-targeted therapeutics and delivery-enabled small molecules
• Utilize Structure-Activity Relationships to prioritize hypotheses, set design criteria, and guide external synthesis efforts
• Evaluate and interpret complex datasets and translate findings into clear, actionable design decisions
• Collaborate closely with biology, structural biology, DMPK, and translational teams to integrate insights into compound design and program strategy
• Prioritize and manage multiple tasks to ensure timelines and deliverables are met
• Maintain high-quality documentation and data management practices
• Present data and strategy clearly to internal teams and senior leadership
• Contribute to intellectual property strategy and filings
• Foster a collaborative, innovative, and high-performance research culture

Qualifications

To perform this job successfully, an individual must be able to perform each essential duty. The requirements listed below are representative of the knowledge, skill, abilities, and prior experience required.

• PhD in Organic Chemistry or a related discipline
• 4+ years of relevant industry experience
• Strong foundation in synthetic organic chemistry and medicinal chemistry, with demonstrated ability to guide compound design, interpret SAR, and apply physicochemical and structural insights leading to optimized drug candidates
• Proven ability to work effectively on multidisciplinary teams in a fast-paced research environment
• Demonstrated track record of progressing compounds towards development
• Exceptional organizational and project management skills, with the ability to manage competing priorities
• Excellent written and verbal communication skills

  Preferred Qualifications

• Experience with antibody-drug conjugates (ADCs), linker-payload systems, or other targeted delivery modalities
• Demonstrated ability to integrate biology-driven insights into chemistry strategy, including payload selection and receptor-mediated uptake strategies
• Track record of meaningful contributions to candidate selection

How you work

• Dare to Succeed: Brings intellectual curiosity and scientific courage to challenge conventional approaches and explore innovative chemistry and delivery strategies. Pursues bold yet data-driven solutions to advance integrin-enabled therapeutics.
• Make an Impact: Takes strong ownership of scientific outcomes, proactively driving decisions and progress with urgency and accountability. Translates complex data into clear actions that move programs efficiently toward development.
• One Pliant: Works collaboratively across disciplines, valuing diverse perspectives to strengthen scientific decisions. Aligns individual contributions with team and company goals to drive collective success.

The annual base salary for this role is $160,000 – $180,000. Individual pay may vary based on additional factors, including, and without limitation job-related skills, experience, work location and relevant education or training. Pliant’s compensation package also includes benefits, equity, and annual target bonus for fulltime positions.

Data Scientist, Developer Productivity

About the role

As part of our growing Data Science and Analytics team, you'll play an instrumental role in Anthropic's mission of building safe and beneficial AI by driving data-informed decision making across the company. This role sits at the intersection of data science, developer experience, and AI tooling — and offers the unusual opportunity to study frontier AI usage from the inside, with the builders themselves as your users.

You'll define how Anthropic understands and improves developer productivity — both through classic software engineering effectiveness measures and through the emerging challenge of understanding AI-augmented development workflows. You'll own the quantitative foundation for how Anthropic's engineers build: what slows them down, what accelerates them, where tooling investments pay off, and how AI-assisted development is changing the shape of engineering work. Your analyses will directly inform infrastructure priorities, tooling roadmaps, and how we think about scaling engineering output as Anthropic grows.

You've worked in cultures of excellence in the past, and are eager to apply that experience to help shape the cultural norms and best practices of a growing data science team as Anthropic continues to scale.

Key responsibilities

• Define key metrics, build measurement frameworks, and maintain core reporting to evaluate developer productivity and engineering effectiveness
• Deep dive into product and user data to derive actionable insights, size opportunities, and influence roadmaps through clear recommendations
• Develop hypotheses and apply rigorous causal inference methods — controlled experiments, synthetic controls — to make actionable recommendations
• Investigate anomalies, conduct root cause analyses, and provide data-driven insights to guide priorities and inform decisions
• Build statistical models, optimization frameworks, and simulations to automate decision-making and operational processes
• Present complex analyses and recommendations to both technical and non-technical stakeholders
• Establish foundational data practices and help scale our analytics infrastructure to support rapid iteration as our products grow

Minimum qualifications

• Working expertise with Python and SQL
• Working expertise with data visualization tools
• Hands-on experience with experimental design, causal inference, statistical modeling, and A/B testing frameworks
• Strong written communication and presentation skills
• Track record of translating complex data into clear, actionable insights for both technical and business stakeholders

Preferred qualifications

• 7+ years of experience in data science or analytics roles
• Direct experience working with developer productivity, infrastructure, performance, or platform teams in rapidly scaling environments
• Deep understanding of distributed systems, cloud infrastructure, and performance engineering, with experience analyzing large-scale system metrics
• Experience applying experimental design and causal inference methods in high-scale technical environments
• Comfort with ambiguity and a track record of creating clarity and driving progress in fast-moving environments
• Experience with AI/ML products, large language models, or developer tools in the AI/ML ecosystem
• Passion for Anthropic's mission of building helpful, honest, and harmless AI

Deadline to apply: None. Applications are reviewed on a rolling basis.

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our New York City office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

The Data Science team at Asana is pivotal in fulfilling our mission by fostering a data-driven approach in shaping both our product and business strategies. In your role on the Marketing Data Science team, you will be the deepest technical expert responsible for using data and scientific techniques to design and build scalable, state-of-the-art solutions to enhance Asana’s marketing effectiveness. You will drive the technical roadmap for data science, collaborating with marketing leadership and the broader Asana data community to uncover new opportunities. You will provide technical leadership and hands-on mentorship, elevating the team's technical bar and influencing overall business strategy through best-in-class modeling and experimental design.

This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.

What you’ll achieve:

• Architect, design, and lead the technical execution for the Marketing Data Science roadmap, serving as the Solution Architect for all core projects including Media Mix Modeling (MMM), User Lifetime Value, Causal Inferences, Multi-touch Attribution, and Spend Optimization engines.
• Act as the primary technical subject matter expert for the Marketing Data Science team, setting the technical bar for modeling quality, code rigor, data pipeline architecture, and solution scalability.
• Collaborate with marketing leadership to pinpoint how data science can be further integrated into Asana's business approach.
• Provide hands-on technical mentorship and guidance to a team of data scientists at varying levels, helping them navigate complex modeling challenges, choose appropriate methodologies, and establish robust ML Ops.
• Develop and standardize MLOps tooling and processes that enable the team to deploy, monitor, and maintain multiple models in production efficiently and reliably.
• Research, prototype, and advocate for emerging capabilities and state-of-the-art models in the marketing data science space, demonstrating their potential benefits and leading their implementation.
• Take on a technical leadership role within the broader Asana Data Community, interacting with Data Engineering and Platform teams to influence the data and MLOps infrastructure required to support marketing data products.

About you:

• Bachelor Degree in Math, Statistics, Computer Science, Engineering a related quantitative field, or equivalent experience
• 6+ years of experience in a data science role, with 2+ years dedicated to technical leadership and mentorship of other data scientists, successfully driving the architecture and execution of large-scale production data science projects
• 4+ years of experience collaborating with Marketing functions on deep technical projects, with extensive experience designing, implementing, and deploying marketing models (e.g. MMM, LTV, MTA, Uplift)
• Expert-level knowledge in advanced statistical modeling, causal inference, experimental design and analysis, and machine learning techniques relevant to marketing effectiveness
• Proven track record developing, deploying, and maintaining scalable production ML solutions and data products
• Technical Stack: Expert proficiency in SQL and Python. Experience with MLOps tools (e.g., MLFlow), statistical languages (e.g., R), and distributed data processing systems (e.g., Spark, Redshift) is a plus
• Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we’ll offer:

Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.

For this role, the estimated base salary range is between $202,000 - $282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.

In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:

• Mental health, wellness & fitness benefits
• Career coaching & support
• Inclusive family building benefits
• Long-term savings or retirement plans
• In-office culinary options to cater to your dietary preferences 

These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.

#LI-Hybrid #LI-AA1

Pinterest is the world's leading visual search and discovery platform, serving over 500 million monthly active users globally on their journey from inspiration to action. As we scale and unify our foundational AI models across every recommendation surface, rigorously measuring the system-level impact of these advances is essential to our ability to ship with confidence and compound gains over time.

We are looking for a Senior Data Scientist to serve as the measurement backbone for Pinterest's foundational model initiatives within the Advanced Technology Group (ATG). In this role, you will design the evaluation frameworks, experimentation strategies, and system-level metrics that quantify how improvements to our largest and most complex models translate into real user and business outcomes. You will work in a highly collaborative and cross-functional environment, partnering with ML Engineers, Applied Scientists, Product Managers, and ML Platform engineers. 

You are expected to develop a deep understanding of Pinterest's recommendation ecosystem, from representation learning to retrieval, ranking, reinforcement learning, and beyond, and bring the analytical rigor necessary to decompose, attribute, and communicate the impact of foundational model changes across this interconnected system. The results of your work will directly influence model investment decisions, launch criteria, and the pace of innovation across ATG and Pinterest.

What You'll Do

• Design and execute system-level measurement frameworks for foundational model improvements spanning offline evaluation benchmarks, online A/B experiments, and longitudinal impact tracking across surfaces.
• Define, and own the success metrics that quantify foundational model value.
• Build causal inference methodologies to isolate the incremental impact of individual model components within a complex, multi-model production system where changes co-occur and interact.
• Work cross-functionally to build relationships, proactively communicate key findings, and collaborate closely with ML Engineers, Applied Scientists, Homefeed and Surface teams to ensure measurement rigor is embedded in every model launch.
• Relentlessly focus on impact, whether through sharpening investment decisions with data, raising the bar for launch criteria, accelerating experimentation velocity, or surfacing hidden inefficiencies in the model ecosystem.

What We're Looking For

• 5+ years of experience analyzing data in a fast-paced, data-driven environment with proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Strong interest and hands-on experience in one or more of: ML system evaluation, recommender system measurement, A/B experimentation at scale, causal inference
• Deep familiarity with large-scale recommendation or ranking systems and their evaluation including an understanding of how representation learning, retrieval, ranking, and re-ranking stages interact and compound in production.
• Experience designing and executing A/B experiments for complex ML systems,  including multi-surface holdouts, metric decomposition, long-run effect estimation, and interference/spillover mitigation.
• Strong quantitative programming (Python) and data manipulation skills (SQL/Spark); experience with ML pipelines, feature stores, and large-scale experimentation platforms.
• Ability to work independently, drive ambiguous projects end-to-end, and operate with high ownership in a fast-moving research-to-production environment.
• Excellent written and verbal communication skills, with the ability to translate complex system-level findings into clear narratives for technical and non-technical partners including leadership-level investment recommendations.
• A team player eager to partner across teams to turn measurement insights into better models and faster launches.

This position is not eligible for relocation assistance.

#LI-NM4

The Opportunity:

Grow Therapy is seeking a Senior/Staff Data Scientist to deepen our understanding of our users and unlock the next era of our growth trajectory. In this role, you will drive insights that get more people successfully onboarded and retained in online therapy, shape how we build our mobile app and digital experiences, and lead the charge on how AI is used alongside therapy. You will also develop marketing and attribution models that help us reach patients more effectively and empower our providers’ success. Your work will directly influence product strategy, experimentation, and long-term investment decisions across the company.

What You’ll Be Doing:

• Lead experimentation and metric development to understand user behavior, optimize onboarding and retention, and guide product direction across web and mobile experiences.
• Build predictive, attribution, and behavioral models that inform marketing strategy, therapist-matching workflows, and future AI-powered features.
• Partner closely with Product, Engineering, Design, and Operations to identify opportunities, quantify impact, and drive roadmap decisions with clear, actionable insights.
• Develop dashboards, analytical frameworks, and self-serve tools that scale data access and empower teams to answer their own product questions.
• Shape Grow Therapy’s AI strategy by designing evaluation frameworks, running model-level experiments, and identifying where AI can improve the patient and provider experience.

You’ll Be a Good Fit If: 

• 5+ years of experience in a quantitative role applying analytics, experimentation, and modeling in a product-focused environment.
• Fluent in SQL and Python, with experience designing A/B tests, building models, and translating complex data into clear recommendations.
  Experience driving product or growth decisions through deep user understanding, funnel analytics, or marketplace dynamics.
• Comfort navigating ambiguity and working cross-functionally in fast-moving environments where data science directly influences strategy.
• Excited about improving access to mental health care and motivated by building AI-enhanced experiences that support therapists and patients.

Role Details:

Employment Type: Full Time, Exempt
Base Compensation: The base compensation range for this position is:

• Hybrid Commitment: $182,000–$228,000 USD USD Annually

This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department off-sites).

The Opportunity:

Grow Therapy is seeking a Staff Data Scientist to deepen our understanding of our users and unlock the next era of our growth trajectory. In this role, you will lead cross-functional, data-driven initiatives and drive insights that get more people successfully onboarded and retained in online therapy, shape how we build our mobile app and digital experiences, and lead the charge on how AI is used alongside therapy. You will also develop and own marketing and attribution models that help us reach patients more effectively and empower our providers’ success. Your work will shape product strategy, experimentation, and long-term investment decisions across the company.

What You’ll Be Doing:

• Lead experimentation and metric development to understand user behavior, optimize onboarding and retention, and guide product direction across web and mobile experiences.
• Build predictive, attribution, and behavioral models that inform marketing strategy, therapist-matching workflows, and future AI-powered features.
• Partner closely with Product, Engineering, Design, and Operations to identify opportunities, quantify impact, and drive roadmap decisions with clear, actionable insights.
• Develop dashboards, analytical frameworks, and self-serve tools that scale data access and empower teams to answer their own product questions.
• Shape Grow Therapy’s AI strategy by designing evaluation frameworks, running model-level experiments, and identifying where AI can improve the patient and provider experience.

You’ll Be a Good Fit If:

• 8+ years of experience in a quantitative role applying analytics, experimentation, and modeling in a product-focused environment, including leading high-impact, cross-functional data science or analytics initiatives.
• Fluent in SQL and Python, with deep experience designing A/B tests, building models, and setting a high bar for translating complex data into clear recommendations for stakeholders at all levels.
• Proven experience owning and driving product or growth decisions through deep user understanding, funnel analytics, or marketplace dynamics, and doing so through influence as well as hands-on work.
• Comfortable navigating ambiguity and working cross-functionally in fast-moving environments where data science directly influences strategy, and aligning multiple teams around shared metrics and insights.
• Excited about improving access to mental health care and motivated by building AI-enhanced experiences that support therapists and patients.

Role Details:

Employment Type: Full Time, Exempt
Base Compensation: The base compensation range for this position is:

• Hybrid Commitment: $200,000–$250,000 USD USD Annually

This role can be hybrid (onsite from our NYC, San Francisco, or Seattle hub location three days per week: Tuesday, Wednesday, Thursday) or fully remote. Both arrangements include travel 2–3 times per year (e.g., company and department off-sites).

The Mission

As CoreWeave continues to solidify its position as the Essential Cloud for AI, we are seeking a visionary VP of Product, Research Training Infrastructure. This executive leader will own the product strategy and engineering execution for the services that power the most ambitious AI research labs in the world. You will bridge the gap between "the metal" and the researcher, delivering a seamless, high-performance environment where frontier models are born.

The Role: Architect of the AI Factory

You will lead the product strategy of our Research Training Stack, focusing on the specialized orchestration, evaluation, and iteration tools required for massive-scale pre-training and post-training. This is a mission-critical role at the intersection of high-performance computing (HPC) and cloud-native agility.

Core Responsibilities

• Frontier Orchestration: Oversee the evolution of SUNK (Slurm on Kubernetes) to provide researchers with deterministic, bare-metal performance through a cloud-native interface.
• Holistic Training Services: Beyond Slurm, drive the development of next-generation orchestrators and automated training-based evaluation frameworks that ensure model quality throughout the lifecycle.
• Post-Training Excellence: Build the infrastructure required for sophisticated Reinforcement Learning (RL) and RLHF pipelines, enabling labs to refine foundation models with maximum efficiency.
• Customer Advocacy: Act as the primary technical partner for lead researchers at global AI labs, translating their "future-state" requirements into actionable product roadmaps.

Requirements: Deep Research & Infrastructure Mastery

• Proven Leadership: 15+ years of experience in engineering leadership, with at least 5+ years managing large-scale infrastructure at a top-tier research lab or an AI-native cloud provider.
• Domain Expertise: Deep, hands-on knowledge of Slurm, Kubernetes, and the specific networking requirements (InfiniBand/RDMA) for distributed training clusters.
• Research Mindset: You likely come from a background supporting frontier model research (pre-training and post-training) and understand the "pain points" of a research scientist.
• Scaling Experience: A track record of delivering mission-critical services on multi-thousand GPU clusters (H100/Blackwell/Rubin architectures).
• Strategic Vision: Ability to define "what’s next" in the AI stack, from automated RL loops to specialized sandbox environments.

Why CoreWeave?

In 2026, CoreWeave is the foundation of the largest infrastructure buildout in human history. We are building AI Factories, not just data centers.

• Silicon-Up Innovation: Work directly with the latest NVIDIA architectures.
• Impact: You will be the architect of the environment that enables the next new discovery.

Velocity: We move at the speed of the researchers we support, bypassing legacy cloud bottlenecks to deliver raw power.

The base salary range for this role is $233,000 to $341,000. The starting salary will be determined based on job-related knowledge, skills, experience, and market location. We strive for both market alignment and internal equity when determining compensation. In addition to base salary, our total rewards package includes a discretionary bonus, equity awards, and a comprehensive benefits program (all based on eligibility). 

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Central Market Management & AI (CMM&AI) team, a key part of the broader Rideshare Experience & Marketplace organization, is essential for maintaining a balanced and efficient marketplace. We do so by developing foundational models, business datasets, and decision-making applications that support a wide range of teams across Lyft. These critical platforms and tools power our pricing / pay strategy, operational alignment, and regional strategies, enabling us to compete effectively in the Rideshare landscape.

Data Scientists in CMM&AI solve the foundational problems that drive Lyft’s marketplace. From forecasting supply and demand to optimizing investments and measuring the ROI of growth levers, our work shapes both automated processes and high-level strategic decisions. Because our challenges are unique to a real-time marketplace, we avoid off-the-shelf solutions in favor of creativity and first-principles mathematical reasoning. We leverage a deep stack of technologies across forecasting, machine learning, inference, and optimization to deliver measurable impact.

As a Senior Data Scientist on the Foundational Models team in CMM&AI, you will operate at the intersection of Machine Learning, Data Science, and Economics to build scalable optimization and modeling systems that directly impact Lyft’s top and bottom lines. You will be hands-on with formulating optimization problems, building ML models, productionizing pipelines, and integrating their outputs within decision-making frameworks. You will collaborate with Product, Engineers, Data Scientists, and Analysts to help define the roadmap and architecture for our next generation of foundational marketplace models that accelerate iterations and drive business efficiency.

Responsibilities:

• Optimization & Modeling
  • Design, formulate, and solve complex mathematical optimization problems that power Lyft’s marketplace decisions across pricing, pay, incentives, and resource allocation.
  • Build, deploy, and maintain production-grade ML and optimization models; collaborate with Software Engineering to integrate algorithms into live systems and establish robust monitoring for model performance and data health.
  • Own the full model lifecycle—from problem framing and prototyping through experimental validation and production deployment—refusing a “build and forget” mentality.
  • Apply first-principles mathematical reasoning to marketplace challenges, choosing the simplest effective solution and building complexity only when incremental value justifies the technical debt.
• Technical Strategy & Execution
  • Drive large-scale technical projects from initial concept to high-impact execution, ensuring alignment with business priorities and Lyft’s overarching goals.
  • Contribute to and influence the multi-quarter technical roadmap for foundational models, helping shape the vision and architecture for next-generation optimization and forecasting systems.
  • Champion high standards for code quality through well-tested, maintainable code and the development of shared team components and libraries.
  • Infuse AI capabilities into existing workflows and demonstrate agility in adopting emerging AI models and techniques to keep Lyft at the forefront of marketplace optimization.
• Stakeholder Partnership & Influence
  • Partner with Data Scientists, Engineers, Product Managers, and Business Partners across lever teams (Pricing, Pay, Driver Engagement, Rider Engagement) to frame problems mathematically and within the business context.
  • Serve as a subject matter expert on optimization and modeling, providing technical guidance and thought leadership to elevate the team’s capabilities.
  • Foster a data-driven culture by presenting actionable insights and recommendations to senior leadership and cross-functional stakeholders.
  • Influence stakeholder roadmaps and advise cross-functional partners on the long-term trade-offs of different algorithmic approaches.

Experience:

• Required:
  • M.S. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
  • 4+ years of hands-on experience developing and deploying optimization and/or machine learning models in a production environment.
  • Advanced proficiency in Python and SQL, with a focus on writing clean, maintainable, and well-tested production code.
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization.
  • Passion for solving unstructured and non-standard mathematical problems using first-principles reasoning.
  • Excellent communication skills and a track record of working closely with Software Engineers, Analysts, and Business Stakeholders to drive decision-making.
• Preferred:
  • Ph.D. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
  • Experience in pricing optimization, marketplace design, and/or resource allocation in a two-sided marketplace environment.
  • Proven track record of delivering measurable business value through the full lifecycle of model development, including experimental design and causal inference.
  • Deep understanding of how various levers (e.g., pricing, incentives, supply positioning) influence marketplace equilibrium and system-wide dynamics.
  • Experience with productionizing algorithms for real-time or near-real-time decision systems.
  • Experience influencing technical roadmaps and advising cross-functional partners on the long-term trade-offs of different algorithmic approaches.
  • Exposure to modern AI/ML frameworks or integration patterns

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention.

As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. 

We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks.

Responsibilities

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
• Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries.
• Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. 
• Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
• Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes
• Drive collaboration and coordination with cross-functional teams

Experience

• M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields
• 2+ years of algorithms experience in a technology company setting
• Proficiency with Python and working in a production coding environment
• Passion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.
• Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models
• Strong verbal and written communication skills with a good track record of collaborating with others to solve a problem

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $140,800 - $176,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Pricing team is a centerpiece of Lyft’s marketplace, determining prices for all rideshare products and supporting new initiatives. Dynamic Pricing & Offer Selection sits at the heart of Pricing, focused on determining optimal prices and ETAs in real-time and balancing supply and demand for our two-sided marketplace to drive both short-term and long-term conversion and retention.

As an Applied Scientist specializing in Machine Learning and Operations Research on this team, you will develop mathematical models and launch algorithms that power these key pricing and ETA decisions. You will leverage your skills to build ML and optimization models and productionalize pipelines that can scale to millions of calls per day while solving critical business problems that have a big impact on the marketplace and rider experience. You will get exposure to a diverse set of real-world problems across optimization, prediction, machine learning, and inference and collaborate closely with teammates and stakeholders across Pricing, from Product Managers to Engineers and Analysts. 

We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions, systems and decision frameworks.

Responsibilities

• Partner with Data Scientists, Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
• Write production quality code. Design, build and deploy production-grade ML and Optimization models. Able to build custom methods and tooling beyond off-the-shelf libraries.
• Perform data analysis and build proof-of-concepts to explore and propose ML and Optimization solutions to both new and existing problems. 
• Evaluate machine learning systems against business goals. Collaborate with Engineers to implement algorithms in live systems and ensure the robustness of the systems
• Establish metrics and development measurement methodologies to monitor the health of our products, as well as the impacts on user and marketplace outcomes
• Drive collaboration and coordination with cross-functional teams

Experience

• M.S. or Ph.D. in Machine Learning, Operations Research, Statistics, Computer Science or other quantitative fields
• 2+ years of algorithms experience in a technology company setting
• Proficiency with Python and working in a production coding environment
• Passion for solving unstructured and non-standard mathematical problems and building impactful machine learning models leveraging expertise in one or multiple fields.
• Strong understanding of machine learning methodologies, with proven experience with building and evaluating optimization or machine learning models
• Strong verbal and written communication skills with a good track record of collaborating with others to solve a problem

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $140,800 - $176,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features.

As a Data Scientist on the Risk Solutions team, you will drive a mission critical to both the safety of our community and the financial resilience of our platform. You’ll partner cross-functionally with Product, Engineering, Actuarial and Claims teams to transform complex data into actionable strategies. You will serve as an analytical lead for claims and road safety initiatives, designing experiments and predictive models aimed at reducing accident frequency and claim severity to optimize long-term risk outcomes. If you are a problem-solver eager to apply high-level data science to real-world safety and financial challenges, this role offers a direct path to high-impact innovation.

Responsibilities:

• Leverage large-scale data and analytic frameworks to identify high-impact opportunities to reduce the total cost of claims. 
• Partner with product managers, engineers, actuaries, claims, and operators to translate data insights into decisions and action
• Construct and fit statistical, machine learning, or optimization models
• Design and analyze online experiments; communicate results and act on launch decisions
• Develop analytical frameworks to monitor business and product performance
• Establish metrics that measure the health of our products, the business, as well as the driver experience
• Collaborate with the Claims team to identify high-impact opportunities where data-driven interventions can reduce the total cost of claims.

Experience:

• Degree in a quantitative field such as statistics, actuarial science, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 5+ years of industry experience in a data science, analytics, or management consulting role.  
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
• Proficiency in SQL and Python
• Experience with insurance claims analytics a plus
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our products and make business decisions. This will involve identifying and scoping opportunities, shaping team priorities, recommending and implementing technical solutions, designing experiments, and measuring the impact of new features.

As a Data Scientist on the Risk Solutions team, you will drive a mission critical to both the safety of our community and the financial resilience of our platform. You’ll partner cross-functionally with Product, Engineering, Actuarial and Claims teams to transform complex data into actionable strategies. You will serve as an analytical lead for claims and road safety initiatives, designing experiments and predictive models aimed at reducing accident frequency and claim severity to optimize long-term risk outcomes. If you are a problem-solver eager to apply high-level data science to real-world safety and financial challenges, this role offers a direct path to high-impact innovation.

Responsibilities:

• Leverage large-scale data and analytic frameworks to identify high-impact opportunities to reduce the total cost of claims. 
• Partner with product managers, engineers, actuaries, claims, and operators to translate data insights into decisions and action
• Construct and fit statistical, machine learning, or optimization models
• Design and analyze online experiments; communicate results and act on launch decisions
• Develop analytical frameworks to monitor business and product performance
• Establish metrics that measure the health of our products, the business, as well as the driver experience
• Collaborate with the Claims team to identify high-impact opportunities where data-driven interventions can reduce the total cost of claims.

Experience:

• Degree in a quantitative field such as statistics, actuarial science, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 5+ years of industry experience in a data science, analytics, or management consulting role.  
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Ability to manage, influence, negotiate, and inspire others in a fast-moving environment
• Proficiency in SQL and Python
• Experience with insurance claims analytics a plus
• Strong oral and written communication skills, and ability to collaborate with cross-functional partners

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Rider team is the heartbeat of Lyft business. Every feature you build translates to a better experience for millions of riders globally. The Rider New Product team is the engine of innovation for Lyft's business. The Rider New Product science team’s mission is to rigorously quantify the value of innovation by applying advanced causal inference to unlock Lyft’s next generation of growth. You will have the autonomy of a startup lead with the data scale of a global tech giant.

This is a high-impact, highly technical role within a core business line. The ideal candidate brings strong applied causal inference intuition, hands-on experience with advanced measurement techniques, and the ability to write clean, efficient production code. You will play a critical role in shaping the future of the Lyft rideshare experience by rigorously measuring the true incremental impact of new product features, shaping critical business decisions, and bridging the gap between cutting-edge applied science research and production-scale product impact.

Responsibilities

• Own complex, open-ended incrementality measurement problems. Translate ambiguous product launches into concrete causal frameworks and experimental designs.
• Lead high-impact Causal Inference initiatives. Drive innovation by introducing advanced measurement techniques to quantify the incremental impact of new rider features.
• Partner deeply with Product, Engineering, and Finance. Define the technical vision for how Lyft evaluates innovation, ensuring that we move beyond simple correlations to understand the long-term drivers of rider behavior and value.
• Design and build production-grade measurement systems. Develop and deploy robust causal models pipelines that balance high scientific rigor with the practical constraints.
• Establish robust evaluation frameworks. Ensure that the "engine of innovation" is steering the business toward sustainable, incremental growth.
• Build reusable science infrastructure. Create internal libraries and best practices for causal discovery and automated measurement.
• Mentor and guide junior/mid-level scientists. Serve as a technical advisor on experimental design, statistical modeling, and fostering a culture of scientific excellence.

Experience:

• Advanced Quantitative Background: Master’s or PhD in Economics, Statistics, Applied Math, Computer Science or equivalent high-impact industry experience.
• 3+ Years of Applied Experience: Proven track record in applied science or data science, with a focus on deploying causal models that drive measurable business outcomes.
• Deep product intuition and hands-on experience with causal methods
• Strong proficiency in Python and SQL.
• Experienced in defining and executing sophisticated evaluation strategies, including advanced experiment design and counterfactual analysis to isolate incrementality.
• Proven ability to align cross-functional partners, influence technical architecture, and challenge scientific assumptions to guide high-level product strategy.
• Excellent ability to articulate complex causal concepts, trade-offs between rigor and speed, and scientific findings to both technical peers and executive stakeholders.
• Preferred Qualifications
  • Demonstrated ability to own high-stakes, open-ended problem spaces, translating vague business questions into rigorous scientific roadmaps.
  • Experience in mentoring other scientists, elevating the bar for technical quality, and establishing best practices for modeling and scientific reasoning.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the New York City area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Central Market Management & AI (CMM&AI) team, a key part of the broader Rideshare Experience & Marketplace organization, is essential for maintaining a balanced and efficient marketplace. We do so by developing foundational models, business datasets, and decision-making applications that support a wide range of teams across Lyft. These critical platforms and tools power our pricing / pay strategy, operational alignment, and regional strategies, enabling us to compete effectively in the Rideshare landscape.

Data Scientists in CMM&AI solve the foundational problems that drive Lyft’s marketplace. From forecasting supply and demand to optimizing investments and measuring the ROI of growth levers, our work shapes both automated processes and high-level strategic decisions. Because our challenges are unique to a real-time marketplace, we avoid off-the-shelf solutions in favor of creativity and first-principles mathematical reasoning. We leverage a deep stack of technologies across forecasting, machine learning, inference, and optimization to deliver measurable impact.

As a Senior Data Scientist on the Foundational Models team in CMM&AI, you will operate at the intersection of Machine Learning, Data Science, and Economics to build scalable optimization and modeling systems that directly impact Lyft’s top and bottom lines. You will be hands-on with formulating optimization problems, building ML models, productionizing pipelines, and integrating their outputs within decision-making frameworks. You will collaborate with Product, Engineers, Data Scientists, and Analysts to help define the roadmap and architecture for our next generation of foundational marketplace models that accelerate iterations and drive business efficiency.

Responsibilities:

• Optimization & Modeling
  • Design, formulate, and solve complex mathematical optimization problems that power Lyft’s marketplace decisions across pricing, pay, incentives, and resource allocation.
  • Build, deploy, and maintain production-grade ML and optimization models; collaborate with Software Engineering to integrate algorithms into live systems and establish robust monitoring for model performance and data health.
  • Own the full model lifecycle—from problem framing and prototyping through experimental validation and production deployment—refusing a “build and forget” mentality.
  • Apply first-principles mathematical reasoning to marketplace challenges, choosing the simplest effective solution and building complexity only when incremental value justifies the technical debt.
• Technical Strategy & Execution
  • Drive large-scale technical projects from initial concept to high-impact execution, ensuring alignment with business priorities and Lyft’s overarching goals.
  • Contribute to and influence the multi-quarter technical roadmap for foundational models, helping shape the vision and architecture for next-generation optimization and forecasting systems.
  • Champion high standards for code quality through well-tested, maintainable code and the development of shared team components and libraries.
  • Infuse AI capabilities into existing workflows and demonstrate agility in adopting emerging AI models and techniques to keep Lyft at the forefront of marketplace optimization.
• Stakeholder Partnership & Influence
  • Partner with Data Scientists, Engineers, Product Managers, and Business Partners across lever teams (Pricing, Pay, Driver Engagement, Rider Engagement) to frame problems mathematically and within the business context.
  • Serve as a subject matter expert on optimization and modeling, providing technical guidance and thought leadership to elevate the team’s capabilities.
  • Foster a data-driven culture by presenting actionable insights and recommendations to senior leadership and cross-functional stakeholders.
  • Influence stakeholder roadmaps and advise cross-functional partners on the long-term trade-offs of different algorithmic approaches.

Experience:

• Required:
  • M.S. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
  • 4+ years of hands-on experience developing and deploying optimization and/or machine learning models in a production environment.
  • Advanced proficiency in Python and SQL, with a focus on writing clean, maintainable, and well-tested production code.
  • End-to-end experience with data, including querying, aggregation, analysis, and visualization.
  • Passion for solving unstructured and non-standard mathematical problems using first-principles reasoning.
  • Excellent communication skills and a track record of working closely with Software Engineers, Analysts, and Business Stakeholders to drive decision-making.
• Preferred:
  • Ph.D. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
  • Experience in pricing optimization, marketplace design, and/or resource allocation in a two-sided marketplace environment.
  • Proven track record of delivering measurable business value through the full lifecycle of model development, including experimental design and causal inference.
  • Deep understanding of how various levers (e.g., pricing, incentives, supply positioning) influence marketplace equilibrium and system-wide dynamics.
  • Experience with productionizing algorithms for real-time or near-real-time decision systems.
  • Experience influencing technical roadmaps and advising cross-functional partners on the long-term trade-offs of different algorithmic approaches.
  • Exposure to modern AI/ML frameworks or integration patterns

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan with company match to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Monthly Lyft credits and complimentary Lyft Pink membership

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

The Rider team is the heartbeat of Lyft business. Every feature you build translates to a better experience for millions of riders globally. The Rider New Product team is the engine of innovation for Lyft's business. The Rider New Product science team’s mission is to rigorously quantify the value of innovation by applying advanced causal inference to unlock Lyft’s next generation of growth. You will have the autonomy of a startup lead with the data scale of a global tech giant.

This is a high-impact, highly technical role within a core business line. The ideal candidate brings strong applied causal inference intuition, hands-on experience with advanced measurement techniques, and the ability to write clean, efficient production code. You will play a critical role in shaping the future of the Lyft rideshare experience by rigorously measuring the true incremental impact of new product features, shaping critical business decisions, and bridging the gap between cutting-edge applied science research and production-scale product impact.

Responsibilities

• Own complex, open-ended incrementality measurement problems. Translate ambiguous product launches into concrete causal frameworks and experimental designs.
• Lead high-impact Causal Inference initiatives. Drive innovation by introducing advanced measurement techniques to quantify the incremental impact of new rider features.
• Partner deeply with Product, Engineering, and Finance. Define the technical vision for how Lyft evaluates innovation, ensuring that we move beyond simple correlations to understand the long-term drivers of rider behavior and value.
• Design and build production-grade measurement systems. Develop and deploy robust causal models pipelines that balance high scientific rigor with the practical constraints.
• Establish robust evaluation frameworks. Ensure that the "engine of innovation" is steering the business toward sustainable, incremental growth.
• Build reusable science infrastructure. Create internal libraries and best practices for causal discovery and automated measurement.
• Mentor and guide junior/mid-level scientists. Serve as a technical advisor on experimental design, statistical modeling, and fostering a culture of scientific excellence.

Experience:

• Advanced Quantitative Background: Master’s or PhD in Economics, Statistics, Applied Math, Computer Science or equivalent high-impact industry experience.
• 3+ Years of Applied Experience: Proven track record in applied science or data science, with a focus on deploying causal models that drive measurable business outcomes.
• Deep product intuition and hands-on experience with causal methods
• Strong proficiency in Python and SQL.
• Experienced in defining and executing sophisticated evaluation strategies, including advanced experiment design and counterfactual analysis to isolate incrementality.
• Proven ability to align cross-functional partners, influence technical architecture, and challenge scientific assumptions to guide high-level product strategy.
• Excellent ability to articulate complex causal concepts, trade-offs between rigor and speed, and scientific findings to both technical peers and executive stakeholders.
• Preferred Qualifications
  • Demonstrated ability to own high-stakes, open-ended problem spaces, translating vague business questions into rigorous scientific roadmaps.
  • Experience in mentoring other scientists, elevating the bar for technical quality, and establishing best practices for modeling and scientific reasoning.

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

Data Science is central to Lyft's products and decision-making. As a Data Scientist on the cross-functional team, you will work in a dynamic environment, tackling a variety of problems from shaping critical business decisions to building algorithms that power our products. We seek passionate, driven Data Scientists to address some of the most interesting and impactful problems in ridesharing.

As a Data Scientist specializing in Algorithms, you will develop mathematical models for the platform's core services, addressing diverse problems in optimization, prediction, machine learning, and inference. On the Fulfillment team, you will collaborate with cross-functional teammates and stakeholders to enhance algorithms for matching rideshare supply and demand in real time and develop product offerings to improve the experiences of Lyft Riders and Drivers.

Responsibilities:

• Leverage data and analytic frameworks to direct creations and improvements of algorithms and models underpinning the team’s systems and products
• Partner with Engineers, Product Managers, and Business Partners to frame problems, both mathematically and within the business context.
• Perform exploratory data analysis to gain a deeper understanding of the problem
• Construct and fit statistical, machine learning, or optimization models
• Write production modeling code; collaborate with Software Engineers to implement algorithms in production
• Design and implement both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions
• Develop measurement methodologies to monitor the health of our products, as well as the impacts on user outcomes and marketplace outcomes
• Drive collaboration and coordination with cross-functional teams

Experience:

• M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
• 2+ years professional experience in a technology company setting
• Proven experience with building and evaluating machine learning models
• Proficiency with Python and working in a production coding environment
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem

Benefits:

• Great medical, dental, and vision insurance options with additional programs available when enrolled
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• 401(k) plan to help save for your future
• In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
• 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
• Subsidized commuter benefits
• Lyft Pink - Lyft team members get an exclusive opportunity to test new benefits of our Ridership Program

Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the San Francisco area is $128,000 -$160,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Location: US remote-friendly or any office location - SF, LA, CHI, NY

The Data Science Team at Reddit is growing and we are looking for experienced Data Scientists to partner with our cross-functional partners (Product, Engineering, Designer, Marketing, Business Development etc.) to help us build and improve the systems that continuously drive our user and revenue growth. 

As a Senior Data Scientist on the team, you will have the opportunity to play a significant role in driving the success of key product areas at Reddit (Consumer, Ads, Safety etc.). You will lead and contribute to defining the product strategy through measurement and metrics design, experimentation and causal analyses, supporting product decisions via deep data analyses, and research. 

This person will be an industry technical leader with a solid technical background, strong business acumen, and excellent cross-functional stakeholders management skills. You will go through a general Data Scientists hiring process and get matched to the product area that best fits your background and interest. 

Responsibilities:

• Develop action-oriented insights to drive the product strategy through observational causal analysis and experiment meta-analysis, and clearly communicate results to stakeholders up to the C-suite to take action based on the recommendations
• Uplevel experimentation practices on the team through guiding design, execution, and deep dive analyses to maximize learnings from A/B tests
• Create new ETLs, tables, dashboards, and other self-serve tools to enable other data scientists and cross-functional partners to find and interact with data seamlessly
• Design, evaluate, and/or measure team-level KPIs to enable quarterly goal setting and demonstrate team impact
• Regularly engage with stakeholders to gather feedback and share progress on work at all stages to ensure alignment between DS and other teams on business goals and outcomes
• Mentor more junior data scientists and business partners in data science best practices and methods to increase data literacy and improve decision making

Required Qualifications: 

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Expertise in querying relational databases (SQL) and programming languages (e.g., R / Python)
• Deep understanding of online experimentation (A/B testing), causal inference, and statistical techniques
• Comfortable in innovative and fast-paced environments, and a bias toward action
• Strong technical communication / data storytelling skills and demonstrated ability to discuss complex topics with technical and non-technical audiences alike
• Able to tackle ambiguous and undefined problems by creating an action plan, getting feedback, and iterating

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote #LI-NH1 

Location: US remote-friendly or any office location - SF, LA, CHI, NY

Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. 

Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes.

As a Staff Data Scientist on the team, you will play an influential role in guiding product strategy through proactively identifying opportunities, conducting exploratory analyses and sharing insights, and driving learning through experimentation.

Responsibilities:

• Help build the long term product strategy by identifying opportunities to attract new users, increase engagement, and drive retention 
• Influence strategic roadmaps through data-driven insights into user behaviors and needs
• Design metrics that help evaluate the health of the business and the success of our products, including any ETL development needed for consistent and robust analysis
• Drive experimentation from design through execution and analysis to maximize learnings and guide future investment decisions
• Build self-serve tools for product and engineering partners that answer common questions and/or increase data literacy in the organization
• Work cross functionally with product, engineering, and design teams to ensure insights make it to the product
• Scale your work to other parts of the data organization through mentoring more junior data scientists, improving processes, and providing perspective on the most important problems

Required Qualifications:

• Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 10+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
• Expert knowledge of SQL and relational databases
• Familiarity with statistical analysis and the preferred programming languages of the team (R / Python)
• Demonstrated ability to influence and guide product strategy with data
• Demonstrated ability to take ambiguous problems and solve them in a structured, hypothesis-driven, data-supported way
• Familiarity with causal inference techniques and causal models
• Excellent communication and experience working with senior leaders / stakeholders 
• Entrepreneurial, self-directed, and enthusiastic about solving problems
• Demonstrated ability to mentor other data scientists and share best practices to elevate the data science practice at Reddit
• Conform in innovative and fast-paced environments, and have a bias toward action.
• Can discuss complex topics with technical and non-technical audiences

Benefits:

• Comprehensive Healthcare Benefits and Income Replacement Programs
• 401k with Employer Match
• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave  

#LI-Remote

Who We are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description: 

Calico is seeking an experienced Process Chemist to join our laboratory-based chemical development team. The ideal candidate brings extensive hands-on experience in process research, route scouting, and scale-up of organic molecules. In this role, you will design, optimize, and execute synthetic processes that enable efficient, safe, and scalable manufacturing of small-molecule intermediates and APIs. This is a lab-focused position requiring strong experimental skills, deep organic chemistry knowledge, and the ability to translate laboratory findings into robust processes. 

Key Responsibilities: 

• Develop, optimize, and troubleshoot synthetic routes for intermediates and drug substance candidates
• Perform laboratory experiments to improve yields, selectivity, throughput, and impurity control
• Conduct detailed reaction analysis using, HPLC, GC, LC-MS, and other analytical techniques
• Perform impurity identification and synthesis
• Identify and mitigate process risks related to safety, scalability, and robustness
• Collaborate with cross-functional partners including analytical chemistry, formulations, and quality assurance 
• Prepare clear, data-driven reports and present experimental results to project teams
• Support technology transfer to contract manufacturing organizations, including review of master batch records and process descriptions
• Maintain accurate lab documentation and adhere to all safety and compliance standards

Position Requirements: 

• PhD in Organic Chemistry or related field with 8+ years of relevant industrial experience in process chemistry
• Strong expertise in synthetic organic chemistry and reaction mechanism fundamentals
• Demonstrated success in developing scalable synthetic processes
• Proficiency with standard analytical instruments and data interpretation
• Excellent problem-solving, organization, and communication skills
• Ability to work independently while contributing effectively to a team environment
• Familiarity with cGMP and ICH guidelines 
• Strong attention to detail and a commitment to high-quality experimentation
• Ability to manage multiple projects and shifting priorities
• A proactive, collaborative mindset with enthusiasm for process improvement
• Must be willing to work onsite 5 days a week

The estimated base salary range for this role is $198,000 - $241,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico is seeking a highly motivated neuroscientist to join a collaborative research team focused on Parkinson’s Disease biology. This is a position for a fearless scientist interested in testing emerging mechanistic and therapeutic hypotheses through the development of fit-for-purpose in vivo models. The candidate should have a broad background in systems neuroscience and neurophysiology. The candidate will work closely with scientists and leaders in translational neuroscience, research physiology, genomics, data science and advanced imaging groups.  The candidate may lead programs from exploratory biology through early drug development.

Key Responsibilities:

• Design, execute and interpret in vivo experiments that may involve stereotactic surgeries, viral delivery, and pharmacology
• Provide scientific leadership for projects involving CROs, external partners, and internal collaborations
• Model creation, licensing, colony planning and maintenance, in coordination with Laboratory Animal Resources and relevant vendors

Position Requirements:

• PhD in biology, neuroscience or related discipline, and 5+ years of relevant post-doctoral or industry experience
• Deep knowledge of neuroanatomy, brain sectioning, and clearing methods
• Proficient in stereotactic surgery
• Track record of linking molecular to functional changes, ideally in models of neurodegeneration and disease pathobiology
• Experience with viral and genetic tools
• Strong teamwork and proactive communication skills
• Self-motivated and able to work independently in a cross-functional team environment
• Proficiency with R, Python, or equivalent platform for data analysis and visualization
• Meticulous with attention to detail
• Must be willing to work onsite 5 days a week

The estimated base salary range for this role is $166,000 - $191,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs. 

Position Description: 

We are seeking an innovative Principal Scientist to bridge the gap between traditional antibody discovery and cutting-edge computational design. In this role, you will serve as the primary scientific liaison between wet-lab antibody team and our machine learning engineers, driving the evolution of our "Design-Build-Test-Learn" cycle.

Acting as both a project leader and technical expert, you will translate complex in silico designs into actionable experimental workflows. You will be responsible for ensuring that computational predictions are rigorously validated and that the resulting biological data is structured to retrain and refine our internal models. We are looking for a deep expert in therapeutic antibody development who is eager to move beyond traditional random screening and champion a rational, data-driven approach to biologic drug discovery.

Position Requirements:

• Ph.D. in molecular biology, biochemistry, computational modeling, structural biology, or related discipline
• 8+ years’ post-PhD experience in antibody/protein engineering within the biotech or biopharma industry
• Demonstrated ability to work intimately with data scientists and ML engineers and able to articulate biological constraints (e.g., immunogenicity, manufacturability) to computational teams and interpret their in silico outputs for experimental validation
• Hands-on proficiency with structural modeling and extensive knowledge in ML protein design tools
• Experience designing experiments specifically to generate high-quality training data for ML models (e.g., focused libraries, systematic mutagenesis) is highly desirable
• Extensive experience in rational design for humanization, affinity/specificity optimization, pH-dependence, and liability removal
• Experience in engineering multi-specific antibodies
• Strong understanding of biophysical characterization to ensure designed molecules are developable therapeutics
• Experience technically managing CROs for in vivo and in vitro discovery of antibodies, gene synthesis, protein production, and screening assays
• Ability to propose novel scientific approaches and solve complex technical hurdles independently
• Must be willing to work onsite 5 days a week

The estimated base salary range for this role is $198,000 - $241,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

We are seeking a highly skilled in vivo scientist to significantly advance neurodegenerative disease research, with a focus on Parkinson's disease. The individual will be instrumental in designing, executing, and interpreting experiments using rodent models to investigate neurological and aging disorders and evaluate therapeutic interventions. This will enhance the Translational Neuroscience team's in vivo research capacity, establish advanced models for due diligence, and test novel drug mechanisms of action. The scientist will also be crucial in modeling novel aspects of neurodegenerative diseases, incorporating human cohort findings, and setting up mechanistic models to test hypotheses from new target discovery.

Responsibilities:

• Develop and characterize novel in vivo models of neurodegeneration and age-related biology
• Design and execute in vivo functional experiments for target validation and mechanistic biology studies
• Conduct broad animal behavioral assessments to characterize neurological phenotypes
• Analyze, interpret, and communicate data and results effectively to the team
• Document data and protocols in accordance with Calico guidelines, maintaining meticulous records of experiments, data, and findings
• Contribute to experimental design, data interpretation, and presentation of results
• Collaborate effectively across multiple functional teams
• Adhere to all animal welfare regulations and institutional guidelines

Position Requirements:

• Ph.D. in Neuroscience, Biology, Pharmacology, or a related field, with 5+ years relevant postdoctoral or equivalent industrial experience
• In Vivo Expertise:
• Experience in live animal surgeries
• Extensive experience with broad animal behavioral assessment techniques
• Expertise in rodent handling, compound treatments, micro sampling, and CNS tissue harvests
• Experience in longitudinal monitoring of behavior and colony maintenance
• Laboratory Skills:
• Practical experience in cellular assays
• Skilled in cells and tissue immunohistochemistry and microscopy, including basic histological techniques for tissue processing, staining, and image analysis
• Analytical & Communication Skills:
• Excellent communication, interpersonal, and organizational skills
• Ability to work independently and collaboratively within multidisciplinary team
• Meticulous with attention to detail
• Must be willing to work onsite 5 days a week

The estimated base salary range for this role is $166,000 - $191,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs. 

Position Description:

Calico is seeking a machine learning research scientist to develop innovative machine learning algorithms to model and design proteins. This person will work with a team of dedicated experimental biologists to design experiments to test and iteratively refine machine learning predictions.

The ideal candidate should be familiar with state-of-the-art machine learning techniques, including language/sequence modeling, representation learning, generative models, and self-supervised learning techniques. Candidates should have experience implementing, extending, and debugging state of the art machine learning models, and have expertise in designing and building robust data infrastructure and tools. Candidates should be independent, self-motivated and be expected to explore relevant ML literature and apply novel approaches to various protein design problems at Calico. Candidates must demonstrate a strong ability to communicate ideas and results through publications and presentations and be able to work cross-functionally to execute on complex projects.

Position Requirements:

• Ph.D. in Computer Science, Computational Biology, or related technical field; OR M.S. in Computer Science, Computational Biology, or related technical field, plus 2+ years industry experience
• Experience in applying deep learning to model biological sequences and structures
• Expert in TensorFlow, PyTorch, and/or JAX
• Strong software engineering skills and substantial expertise in Python
• Track record of outstanding communication and collaboration in a cross-functional environment
• Strong analytical and quantitative skills
• Must be willing to work onsite at least four days a week

Nice to Have:

• Domain expertise in computational biology, biochemistry or structural biology
• Familiarity with state of the art structure modeling tools such as AlphaFold
• Public recognition in the field, e.g. via scientific publications or success in machine learning competitions
• Prior experience working with biologists
• Prior experience working as an ML Engineer/Scientist

The estimated base salary range for this role is $170,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

Calico is seeking a machine learning scientist to join a research group investigating how genome sequence determines regulatory function and how dysregulation of these programs drives aging. We develop sequence-based deep learning models that predict gene expression, chromatin accessibility, and other functional readouts directly from DNA. We use these models to interpret human genetic variation, map causal regulatory mechanisms, and identify promising intervention points.

This work builds on a sustained research program at the intersection of deep learning and regulatory genomics, including:

• Avsec, Ž. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat Methods 18, 1196–1203 (2021).
• Yuan, H. & Kelley, D. R. scBasset: sequence-based modeling of single-cell ATAC-seq using convolutional neural networks. Nat Methods 19, 1088–1096 (2022).
• Linder, J., Srivastava, D., Yuan, H., Agarwal, V. & Kelley, D. R. Predicting RNA-seq coverage from DNA sequence as a unifying model of gene regulation. Nature Genetics (2025).

Additional research can be found here.

Position Responsibilities:

• Design and train deep learning models for biological sequence analysis, with emphasis on gene regulation, single-cell genomics, and variant interpretation
• Partner with experimental scientists to connect model predictions to biological mechanisms — designing validation experiments, analyzing large-scale genomics data, and translating computational findings into actionable biological insights
• Communicate research through publications, open-source software, and public-facing tools

Position Requirements:

PhD in computational biology, bioinformatics, computer science, or a related field, and 0-5 years (for Scientist level) or 5+ years (for Senior Scientist level) of additional training in an industry or academic setting, with a strong publication record

• Deep expertise in machine learning with solid grounding in algorithms, data structures, and statistics
• Substantive knowledge of molecular biology and genetics; familiarity with genomic data types and public data resources
• Hands-on experience analyzing genomics sequencing data, ideally including single-cell assays
• Fluency with modern AI-assisted development and research tools (e.g., LLM-based coding assistants, literature synthesis), with a habit of proactively integrating new tools to accelerate scientific workflows
• A collaborative disposition, strong follow-through, and comfort working at the interface of computation and experiment
• Must be willing to work onsite at least four days per week

The estimated base salary range for this role is $170,000 - $233,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

The Associate Director, Clinical Scientist at Calico is responsible for the planning and execution of the translational and clinical development plans and protocols for several projects across therapeutic areas, related to Calico’s mission to improve human healthspan by understanding aging and age-related diseases. The successful candidate will participate in and drive the development of clinical strategies for assigned program(s)/indication(s) and should be able to support novel and innovative clinical plans while ensuring a positive and collaborative team environment.

Responsibilities:

• In coordination with the Head of Clinical Science and/or Medical Director(s), leads or represents the Clinical Science function in cross-functional project and study teams that develop and execute the clinical development plan to translate preclinical mechanistic data to humans for novel aging-related targets
• Authors clinical sections of assigned protocols from Phase 0 through Phase 2, collaborating with other functions required for protocol development, including Research, Biomarkers, Clinical Operations, Regulatory Affairs, Clinical Pharmacology, Biometrics, Pharmacovigilance, Toxicology, and Medical Writing
• Contributes to the design and execution of experimental medicine studies to demonstrate proof-of-mechanism of novel targets in aging and age-related diseases
• Interfaces with academic investigators to assist in execution of Investigator initiated trials
• Contributes to and/or reviews relevant study documents including Investigational Brochures, Clinical Study Reports, Statistical Analysis Plans, Operations/Technical Manuals, IND/CTAs, case report forms and data tables, listings and figures, CSRs
• Trains CROs and study site personnel on assigned protocols and addresses protocol queries as they arise
• Participates in the assessment of CROs and study vendors

Position Requirements:

•  BS/MS in a relevant scientific discipline with 8+ years or PhD/PharmD with 5+ years of experience in early clinical drug development in the biotech/pharmaceutical industry performing the responsibilities described above
• Experience in early clinical trial methodology (Phase 0, Phase 1, Phase 2) and knowledge of drug development process and clinical deliverables from IND through clinical proof-of-concept
• Excellent understanding of clinically relevant ICH GCP guidance, FDA and EMA regulations
• Ability to perform role responsibilities largely independently
• Proven leadership skills and ability to bring out the best in others on a cross-functional team
• Able to provide effective leadership through influence across organizations on partnered programs
• Detail-oriented mindset with excellent oral and written English communication skills 
• Must be willing to work onsite at least 4 days a week

The estimated base salary range for this role is $238,000 - $245,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

The Medical Director/Senior Medical Director at Calico will report to the Head of Clinical Sciences and will be responsible for providing strategic input to the translational and clinical development of projects related to Calico’s mission to improve human health span by understanding aging and age-related diseases. This position is focused on neurologic/neuropsychiatric indications.

Position Responsibilities:

• Leads cross-functional teams which develop the strategy to translate preclinical mechanistic data to humans and to develop translational biomarkers for novel targets in neurological/neuropsychiatric indications
• Actively interfaces with research and drug development leaders, at Calico and outside of Calico, to inform disease indication strategies for novel targets
• Utilizes clinical expertise to guide the development and utilization of preclinical models in close collaboration with discovery and biomarker scientists at Calico and Calico’s business partners
• Works closely with other drug developmental functional areas to shape new clinical programs at multiple points in their evolution, with an emphasis on translational/early clinical development (Phase 0 through Phase 2)
• Designs and executes experimental medicine studies to demonstrate proof-of-mechanism of novel targets in neuropsychiatric diseases
• Designs and executes early clinical development plans to demonstrate proof-of-concept in various neuropsychiatric indications
• Provides scientific/medical content and other input as appropriate for protocols, Investigator Brochures, Clinical Study reports, regulatory submissions and responses, and other program documents

Position Requirements:

• Scientifically minded Physician (M.D.) or Physician-Scientist (M.D./Ph.D.)
• At least 5 years of translational, clinical trial, or drug development experience in the biotech/pharmaceutical industry, academia, or equivalent
• Board-certified/eligible in Neurology and/or Pediatric Neurology highly preferred
• Clinical/translational research and/or drug development experience across various neuropsychiatric disease areas
• Medical knowledge in treating patients across various neuropsychiatric or neurological indications
• Working knowledge or direct experience in early clinical trial methodology (Phase 0, Phase 1, Phase 2)
• Proven leadership skills and ability to bring out the best in others on a cross-functional team
• Able to provide effective leadership through influence in a highly matrixed environment, including various drug development functions within Calico and its development partners
• Must possess excellent oral and written English communication skills
• Must be willing to work onsite at least 4 days a week

The estimated base salary range for this role is $374,000 - $435,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to increase our understanding of the biology that controls human aging. Calico will use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, academic and industry partners, and vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description:

The Cellular Models and Assay Technologies (CMAT) lab and Microscopy group at Calico are looking for an innovative, technology-driven Scientist to join our teams. This role offers a rare chance to push the boundaries of microscopy and spatial biology within a biotech environment, where novel technologies can be rapidly translated into biological insights that directly inform therapeutic strategy. In collaboration with Biology subject matter experts, the successful candidate will invent, adapt, and apply advanced microscopy techniques to unravel the mechanisms underlying age and age-related disease. A primary area of focus will be the integration of Laser Capture Microdissection (LCM) with proximity biotinylation, in order to map molecular environments within cells and tissues. By combining these with fluorescent biosensors and morphological profiling, you will aim to identify and isolate specific cellular states for deeper phenotyping. 

This hands-on role requires deep expertise in Microscopy, Image Analysis, Cell and Tissue Biology, alongside the ability to develop or implement novel methods as needed. This role will evolve as scientific questions demand, and we are looking for a curious, versatile and proactive scientist who takes an active role in the evolution and expansion of their role. 

Responsibilities:

• In collaboration with other Microscopy and Image Analysis experts, deploy cutting edge technologies to accelerate diverse projects across Calico
• Apply Laser Capture Microdissection (LCM) to isolate specific cell populations or morphological features from cell cultures and tissue sections for downstream multiomics analysis
• Accelerate LCM workflows through automated image analysis and segmentation
• Design and optimize functional reporters in cells and tissues, e.g. proximity biotinylation, to map protein-protein interactions, and fluorescent biosensors to track cellular response to perturbation
• Continuously explore this ever-evolving field and invent and/or implement novel systems as they become available

Position Requirements:

• Ph.D. in Cell Biology, Bioengineering, Biophysics, or a related field with 3+ years of post-doctoral or industry experience
• Extensive hands-on experience with complex fluorescence microscopy techniques (e.g. laser capture microdissection, smart microscopy, light sheet, live cell imaging, super-resolution, etc.)
• Track record of developing or adapting novel microscopy methods to uncover biological insights
• Demonstrated ability in quantitative image analysis, utilizing commercial software (e.g., Imaris, Arivis), open-source tools (e.g., FIJI, CellProfiler), and custom solutions (e.g., Python)
• Experience with functional reporter systems in cells and/or tissues (e.g., proximity biotinylation, fluorescent biosensors) and demonstrated ability to rapidly adopt new techniques
• Experience with mammalian cell culture and stable cell line generation with a diversity of delivery systems
• Ability to operate independently, define experimental strategies, and prioritize multiple concurrent projects in a fast-paced environment
• Exceptional interpersonal and communication skills and effective collaboration across functional groups
• Must be willing to work onsite 5 days per week

Nice to Have:

• Demonstrated proficiency in Laser Capture Microdissection (e.g. Leica LMD) applications in a diversity of cell and tissue types
• Hands-on experience with proximity biotinylation techniques (i.e. BioID, APEX2, TurboID, BAR), including antibody conjugation strategies, fusion protein design, labeling kinetics optimization, and streptavidin-based enrichment
• Hands-on experience with development, optimization, and application of fluorescent sensors and biosensors
• Familiarity with custom microscope hardware and control software
• Experience with complex cell culture models (e.g. primary culture, iPSC-derived neurons, microglia)
• Experience with multiplex immunofluorescence and histological techniques, including tissue processing (FFPE and OCT blocks), cryosectioning, human tissues and patient-derived samples

The estimated base salary range for this role is $156,000 - $191,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Who We Are:

Calico (Calico Life Sciences LLC) is an Alphabet-founded research and development company whose mission is to harness advanced technologies and model systems to deepen our understanding of the biology that controls human aging. Calico aims to use that knowledge to devise interventions that enable people to lead longer and healthier lives. Calico’s highly innovative technology labs, its commitment to curiosity-driven discovery science, and, with academic and industry partners, its vibrant drug-development pipeline, together create an inspiring and exciting place to catalyze and enable medical breakthroughs.

Position Description: 

We are seeking a highly motivated and creative Scientist/Senior Scientist, Aging Biology to join our Translational Medicine team. This role is pivotal in elucidating the mechanism of action (MOA) of therapeutic targets within our aging biology pipeline. The successful candidate will be responsible for defining the molecular and cellular pathways that are fundamental to the program's biology. This role is critical for translating novel in vivo findings into a deep mechanistic understanding to guide its path toward clinical development. The ideal candidate will bring deep expertise in cell biology, MOA studies, and complex signaling pathways to this challenge.

Responsibilities:

• Independently design and lead experimental strategies to elucidate the molecular and cellular mechanisms of action for aging targets and biomarkers, generating insights that guide program direction
• Conduct in vitro and ex vivo studies to investigate target biology in key aging-related processes, including stem cell function, tissue repair, and signaling or transcriptional regulation
• Compare acute and chronic pathway modulation in tissue injury and aging models to understand how stress responses and repair mechanisms evolve with age
• Investigate the molecular drivers of in vivo phenotypes in preclinical aging models to identify biomarkers and translatable mechanisms relevant to clinical development
• Collaborate with in vivo pharmacology and biomarker teams to select and leverage preclinical models that best probe target biology
• Partner with cross-functional groups (e.g., Biomarkers, Genomics, Protein Sciences) to integrate multi-omic datasets and build a comprehensive mechanistic framework
• Analyze, interpret, and present complex data and strategic recommendations to internal project teams and senior leadership
• Maintain rigorous experimental documentation and contribute to internal reports, publications, and regulatory submissions

Position Requirements:

• Ph.D. in Cell Biology, Molecular Biology, Physiology, or a related field, with 2-5 years (for Scientist level) or 5+ years (for Senior Scientist level) of relevant industry or post-doctoral experience
• Demonstrated expertise in designing and executing complex experiments to elucidate mechanisms of action in age-related disease models
• Strong hands-on experience with a range of cellular and molecular biology techniques (e.g., primary cell culture, flow cytometry, single-cell RNAseq, qPCR, Western blot, ELISA, functional assays)
• Proven ability to think critically and solve complex biological problems
• Strong data analysis skills and proficiency with Prism or similar software
• Exceptional organizational skills and meticulous attention to detail, with a proven ability to manage complex projects
• Strong teamwork and communication skills, with an ability to collaborate effectively in a cross-functional environment
• Flexible, able to respond quickly to shifting priorities and to multitask
• Must be willing to work onsite five days per week

Nice to Have:

• Working knowledge of formulation approaches for various routes of administration, including intravenous (IV), subcutaneous (SC), intraperitoneal (IP), and oral
• Familiarity with in vivo models of metabolic or fibrotic disease
• Expertise in mesenchymal or hematopoietic stem cell biology, fibrosis, or tissue repair
• Experience with R or Python for data integration and visualization
• Background in growth factor signaling, extracellular matrix biology, or proteomics

The estimated base salary range for this role is $156,000 - $191,000. Actual pay will be based on a number of factors including experience and qualifications. This position is also eligible for two annual cash bonuses.

Senior Manager, Data Science

Portfolio Management and Loss Mitigation

The Role: 

SoFi is seeking an inspirational and deeply experienced Senior Manager to lead the Portfolio Management and Loss Mitigation function in our Risk Data Science team. Reporting to the Head of Risk Data Science, this role will lead the development, deployment, and governance of portfolio management and loss mitigation models for all credit products.

The ideal candidate is a hands-on leader who can transition the team from traditional modeling to next-generation machine learning platforms, leveraging emerging data sources (e.g., cash flow, alternative bureaus) to significantly improve portfolio performance, reduce losses, and ensure rigorous adherence to Model Risk Management (MRM) standards. This role requires exceptional organizational leadership, an ability to influence stakeholders, and proven success in delivering complex models into a regulated production environment.

What You'll Do: 

• Portfolio Management and Loss Mitigation Excellence: Directly oversee the development and deployment of Next Generation models designed to manage and mitigate portfolio losses while maintaining loss guardrails.
• Drive Next-Generation Capabilities: Incorporate industry trends and advanced techniques (NLP, Graph Mining, LLMs, Deep Learning) to solve complex, high-impact risk problems where established principles may not fully apply.
• Alternative Data Strategy: Spearhead the evaluation and integration of alternative data sources (Macro-Economic variables, tri-bureau, LexisNexis, cash flow data) to enhance predictive power across all credit products.
• Lead the current team of high-performing Staff and Senior Data Scientists. Recruit, mentor, and foster talent through deliberate interactions, succession planning, and creating a high-accountability, low-ego culture.
• Model Risk Management (MRM): Act as the primary owner for all models in the portfolio, ensuring robust documentation, monitoring, and successfully navigating the 2nd Line of Defense (2LOD) review and approval process (SR 11-7 familiarity is mandatory).
• Stakeholder Alignment: Interact and negotiate with senior management and external stakeholders to reconcile competing views and drive critical, high-impact business decisions.
• Automation and Efficiency: Lead efforts to automate model monitoring and governance processes to create scalable and auditable infrastructure.

What You'll Need:

• Experience: 8+ years of progressive experience in credit risk, modeling, and data science within a regulated financial institution (FinTech, Bank, or similar), with at least 3 years in a people management role, managing technical staff.
• Education: Master’s or Ph.D. degree in a quantitative field (Statistics, Computer Science, Engineering, Operations Research, etc.).
• Technical Acumen: Deep expertise in advanced statistical and machine learning modeling techniques (e.g., Gradient Boosting, Deep Learning, Causal Inference).
• Regulatory Knowledge: Detailed working knowledge of model risk management standards (e.g., SR 11-7) and the ability to operate within a highly regulated environment.
• Tools & Platforms: Expert-level proficiency in Python (PySpark, scikit-learn, TensorFlow/PyTorch) and SQL/data warehouse technologies (e.g., Snowflake, Hive). Familiarity with modern MLOps platforms and cloud computing (AWS).
• 3+ years of progressive people management experience is required, including the ability to recruit, mentor, and foster talent within a team of high-performing Staff and Senior Data Scientists.
• Communication: Ability to distill highly complex analytical concepts into clear, concise, and compelling narratives for non-technical leadership.

Staff Software Engineer - AI Research Infrastructure

P-1215

At Databricks, we are obsessed with enabling data teams to solve the world’s toughest problems, from security threat detection to cancer drug development. We do this by building and running the world’s best data and AI platform so our customers can focus on the high-value challenges that are central to their own missions.

The Databricks AI Research organization enables companies to develop AI models and agents using their own data, with technologies ranging from post-training open source LLMs to developing advanced multi-agent architectures. Databricks AI does so by producing novel science and putting it into production. Databricks AI is committed to the belief that a company’s AI models and agents are just as valuable as any other core IP, and that high-quality AI should be available to all.

Job Description

As a Staff Software Engineer, AI Research Infrastructure, you will be developing and running the research stack that powers Databricks AI Research. You will design and build services that schedule, orchestrate, and observe large‑scale training and inference experiment workloads across thousands of GPUs, improve our dev tooling and ensure that researchers can iterate quickly without sacrificing reliability, efficiency, or security.

You’ll partner closely with research scientists, ML engineers, and platform teams to turn experimental workloads into robust, repeatable pipelines, and to push the limits of what our infrastructure can support.

The Impact you will have

As a Staff Software Engineer on the AI Research Infra Team at Databricks, you will: 

• Design and implement infrastructure that supports large‑scale experiments, data processing, and model training (e.g., HPC clusters, GPU fleets, or cloud‑based systems)
• Enable researchers to go from idea to large‑scale experiment in minutes, not days, by building powerful abstractions for job submission, scheduling, and monitoring.
• Create tooling that improves research developer productivity, such as experiment management systems, CI/testing infrastructure for research code, and workflows that reduce iteration time.
• Influence the long‑term roadmap for research computation, shaping how Databricks AI Research train, evaluate, and ship models to customers.
• Serve as a technical mentor and force multiplier for other engineers working on compute, infra, and AI systems.

What We Look for

• BS/MS or PhD in Computer Science or related field
• 5+ years of software engineering experience, including substantial time working on large‑scale distributed systems or infrastructure.
• Have deep experience with building and operating distributed systems, data pipelines, or large‑scale backend services, ideally involving GPUs, clusters, or major cloud providers.
• Are proficient in one or more systems programming languages (e.g., C++, Rust, Go, Java, Scala) and can design, implement, and debug complex services.
• Have built or significantly contributed to cluster schedulers, resource managers, or large‑scale job orchestration systems (e.g., Kubernetes, Slurm, Ray, custom internal systems).
• Understand modern ML training and inference workflows (e.g., distributed training, model parallelism, fine‑tuning, evaluation), even if you’re not primarily a research scientist.
• Can move fast and be pragmatic in getting things done, while caring about operational excellence. Have driven complex systems from prototype to stable, well‑owned services.
• Communicate clearly with both researchers and engineers, and enjoy translating between research needs and infra realities.

Your impact at LILA

We’re building a talent-dense, high-agency research team to develop the next generation of learning systems and reasoning algorithms for agentic LLMs. Our work sits at the intersection of large language models, post-training, and scientific reasoning, with the goal of enabling systems that learn from experience, reason effectively, and improve through interaction.

Scientific domains present a distinct set of challenges that make this problem uniquely hard. Feedback is sparse and delayed — experiments take days or weeks, not milliseconds. Ground truth is expensive or contested. Distribution shift is structural, as instruments, techniques, and knowledge bases evolve continuously. The hypothesis space is vast and reward signal is thin. Existing benchmark do not capture these nuances. The goal is to build systems that can operate effectively in this scientific regime.

This role spans a few complementary directions. Candidates are expected to bring deep expertise in one (ore more) of the following areas. In the event of cross-track expertise, please select the one you align to the most. Our interview process will be catered to verifying the chosen expertise area.

Expertise Area 1 — Agentic system building

Focus: Build systems that autonomously propose, execute, and verify scientific hypotheses over long time horizons.

• Create and analyze long-running auto-research systems that propose and verify hypotheses
• Design planning frameworks for agentic systems operating over long, sparse feedback loops
• Design memory architectures that allow agents to build and retrieve structured knowledge over time
• Explore algorithms in recursive self-improvement, multi-agent coordination, and continual learning

Expertise Area 2: Distillation

Focus: Translate strong inference-time behaviors and reasoning traces into efficient, trainable models.

• Develop distillation strategies from large or ensemble models into deployable systems
• Research methods for self-improvement, including iterative self-distillation and critique loops
• Investigate how to preserve generalization and reduce catastrophic forgetting through the distillation process

Expertise Area 3 — Scalable experience generation

Focus: Develop inference-time algorithms and synthetic data pipelines that generate high-quality training signal for scientific reasoning.

• Design and benchmark inference-time search, sampling, and verification strategies
• Propose new techniques in synthetic environment creation and curriculum learning
• Develop synthetic data generation strategies that capture high-quality scientific reasoning for agentic model training
• Measure the end-to-end impact of inference-time improvements on real scientific tasks

What you’ll need to succeed:

• An advanced degree in computer science, machine learning, or a related field, or or comparable experience
• Strong foundation in LLMs and empirical research
• Experience designing and executing rigorous ML experiments, including benchmarking and ablations
• Experience working with large-scale training or evaluation pipelines
• Ability to define and pursue research directions in open-ended, rapidly evolving spaces
• Strong collaboration and communication skills across research and engineering teams

Bonus points for:

• Experience with synthetic data generation, distillation, or self-improvement loops
• Familiarity with reinforcement learning (e.g., RLHF, on-policy methods)
• Experience with planning, search, or decision-making systems at scale
• Experience in building agentic systems with tool use, or multi-agent workflows
• Background in program synthesis, coding benchmarks, or long-horizon tasks
• Experience building evaluation frameworks or large-scale benchmarks

Scientific rigor & persistence:

• You take a principled approach to experimentation, with careful baselines, ablations, and evaluation design
• You are motivated by understanding why systems work, not just improving metrics
• You prioritize clarity, reproducibility, and intellectual honesty in research
• You are comfortable working through long, nonlinear iteration cycles
• You operate effectively in ambiguous, fast-evolving research environments

Your Impact at LILA

Lila is building a platform where AI and automation co-evolve to solve the hardest problems in medicine. Within Life Sciences AI (LSAI), the AI for Protein Engineering team develops and uses the generative and predictive models that drive Lila's biomolecule design programs from in silico hypothesis to wet-lab validated lead.

We are seeking a Senior or Principal Scientist to join this team as a senior IC focused on antibody design and engineering. You will develop and execute the methods and workflows that ensure successful completion of antibody campaigns. Scope may expand to additional modalities such as enzymes and peptides as needs evolve.

This role sits at the bilingual edge of ML and biology. You will own biological understanding of campaign needs and partner closely with the Life Science Research team to design and validate computational predictions in the lab. You will shape the technical agenda for AI protein engineering at Lila and represent that work both internally and to the broader research community.

What You'll Be Building

• Develop and own protein design and engineering workflows for antibody campaigns, including de novo design, affinity maturation, and developability optimization
• Execute design workflows end-to-end for active campaigns and deliver wet-lab-validated leads against program milestones
• Translate campaign requirements — epitope selection, affinity targets, biophysical constraints, and developability criteria — into well-defined ML problems and design specifications
• Adapt and extend state-of-the-art AI methods (generative models, protein language models, structure-conditioned design) to the specific demands of antibody and broader biomolecule engineering
• Partner with the Life Science Research team on design validation, building active learning loops where wet-lab data refines and improves model performance
• Expand the protein engineering platform to additional modalities such as enzymes and peptides as needs evolve

What You’ll Need to Succeed

• PhD in Computational Biology, Computer Science, Machine Learning, Biophysics, or a related quantitative field
• Proven track record of successful design of wet-lab-validated biomolecules through AI, with industry experience strongly preferred
• Deep ML expertise with the ability to modify and adapt state-of-the-art AI approaches for protein engineering, not just apply them off-the-shelf
• Strong fluency across both ML and protein biology, with hands-on understanding of antibody design
• Demonstrated ability to drive a research and engineering program independently, from problem definition through experimental validation and iteration
• Track record of close collaboration with experimental scientists and clear communication across the ML/biology boundary

Bonus Points For

• Direct experience designing antibodies, nanobodies, or other therapeutic proteins for clinical or therapeutic pipelines
• Experience with structure prediction, generative protein design (diffusion, flow-matching, or similar), and protein language models in a production research setting
• Experience in structural biology and conformational dynamics
• Experience extending design methods to additional modalities such as enzymes, peptides, or other engineered biomolecules
• High-impact publications or open-source contributions in AI for Science (NeurIPS, ICML, ICLR, Nature Methods, Nature Biotechnology, or equivalent)
• Experience designing or operating active learning loops between computational design and high-throughput experimental validation

Position

Manifold's AI team is actively training protein foundation models on our proprietary experimental datasets. Our generative antibody design model, mBER, has already demonstrated controllable de novo binder design across multiple million-scale screening campaigns, and the team is now scaling foundation model capabilities to push well beyond current performance. We are looking for an AI/ML Scientist to join this effort. You will work alongside our existing model training team to accelerate the development of foundation models fine-tuned on Manifold's data, bringing additional depth in pre-training methodology, architecture development, and large-scale training. Your work will directly improve mBER's design capabilities and unlock new modeling paradigms for the broader team. You'll own foundation model projects end-to-end, from architecture selection and training infrastructure to evaluation against real experimental outcomes, while contributing to the team's shared research agenda.

This is an on-site role and can be based in either Boston, Massachusetts or San Francisco, California. Please only apply if you reside in these cities or are open to relocate. 

Responsibilities

• Advance the team's ongoing foundation model training efforts—pretraining, fine-tuning, and evaluating folding, docking, language, and generative design models on Manifold's proprietary experimental data
• Bring depth in training methodology, architecture selection, and optimization to complement the existing team's expertise
• Develop and scale training pipelines for distributed, multi-GPU and multi-node training runs
• Integrate foundation model outputs into mBER to improve binder design success rates and enable new design capabilities
• Design and execute ML experiments with clear hypotheses, rigorous evaluation frameworks, and systematic analysis
• Establish best practices for mixed-precision training, gradient checkpointing, and computational efficiency at scale
• Produce clear documentation and analysis supporting architecture and training decisions

Required Qualifications

• Demonstrated experience pretraining and/or fine-tuning protein foundation models (folding, docking, language models, or generative design) with published or otherwise demonstrable results
• Strong familiarity with AlphaFold architecture and training methodology
• 2+ years of hands-on experience with PyTorch and/or JAX for deep learning
• Experience with large-scale model training: distributed training, multi-GPU/multi-node setups, mixed precision, gradient checkpointing
• Solid understanding of deep learning architectures (transformers, attention mechanisms, diffusion/flow matching) and optimization techniques
• Experience working with protein structure data (PDB, mmCIF) and/or protein sequence datasets
• Strong statistical analysis and experimental design skills
• Proficiency in Python scientific computing stack (NumPy, Pandas, scikit-learn)
• Self-directed researcher who can balance guidance with independence
• Excellent written and verbal communication skills for cross-functional collaboration

Preferred Qualifications

• Experience with protein generative design methods (e.g., RFdiffusion, ProteinMPNN, flow matching approaches)
• Experience with protein language models (e.g., ESM family)
• Published research in computational biology, protein design, or structural biology
• Experience training on proprietary or domain-specific biological datasets
• Familiarity with Ray for distributed computing
• Experience with Kubernetes (EKS) and cloud computing platforms (AWS)
• Knowledge of protein engineering, directed evolution, or structural biology wet lab techniques
• Experience working with agentic AI coding tools for fast, parallelized execution of modeling experiments
• Previous biotech/pharma industry experience

This Role Might Be Perfect For You If:

• You have deep experience training protein foundation models and want to apply that expertise to some of the richest proprietary experimental datasets in the field
• You're excited about pushing beyond public model performance by leveraging unique, large-scale in vivo screening data
• You thrive in high-ownership roles where you can drive research direction while collaborating with a tight-knit, world-class team
• You want your models to directly impact real drug discovery programs

If you're excited to train the next generation of protein foundation models on uniquely powerful experimental data, please reach out to careers@manifold.bio.

Base Salary Range: $140,000-225,000

This reflects the typical offer range for this role, based on experience, role scope, and internal equity. Final compensation decisions are made using a consistent leveling framework and consider the candidate’s experience, interview performance, and expected impact.

This role is eligible for:

• Annual performance-based target bonus
• Stock options
• Comprehensive medical, dental, and vision coverage
• 401(k) plan
• Flexible paid time off and holidays
• Perks including on-site gym, onsite lunch, and commuter support

Our compensation ranges are reviewed annually to ensure alignment with market trends and internal equity.

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies—from the world’s largest enterprises to the most ambitious startups—use Stripe to accept payments, grow their revenue, and accelerate new business opportunities. Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

Our Data Science team partners deeply with teams across Stripe to ensure that our users, our products, and our business have the models, data products, and insights needed to make decisions and grow responsibly. We’re looking for data scientists with a passion for analyzing data, building machine learning and statistical models, and running experiments to drive impact.  Our work is broad and varied, influencing how our products work (e.g. understanding user needs, preventing fraud, or optimizing charge flows), how our business works (forecasting key outcomes, managing liquidity, quantifying risk exposure), how our go-to-market motions operate (designing growth experiments, optimizing marketing investments, refining sales processes, and estimating causal effects), and everything in between. We have a variety of Data Science roles and teams across Stripe and will seek to align you to the most relevant team based on your background.

What you’ll do

About the internship experience

Our internship program provides the opportunity to work on meaningful business initiatives that will grow the GDP of the internet. Through the internship, you will work with many systems and technologies, gain experience in working with large datasets and analytical methodologies/tools to help us better understand our users and build better products. 

Each intern has a dedicated mentor, and every intern project is part of the team's roadmap that will directly contribute to Stripe's mission. As you collaborate with industry experts on initiatives that expand global commerce, you will develop a strong first-hand understanding of the role analytics plays in steering business strategy and results.

We're not just focused on your immediate contributions; we're invested in your growth. Stripe sees this internship as an opportunity to grow your technical expertise and facilitate personal development, preparing you for a career in the tech industry.

Responsibilities

You will:

• Partner closely with Data Scientists, Data Analysts, and business partners to drive business impact through rigorous analytical solutions
• Apply machine learning, causal inference, or advanced analytics on large datasets to: i) measure results and outcomes, ii) identify causal impact and attribution, iii) predict the future performance of users or products, to drive business success
• Influence business actions and strategy by developing actionable insights through metrics and dashboards.
• Drive the collection of new data and the refinement of existing data sources.
• Learn quickly by asking great questions, finding how to work with your mentor and teammates effectively, and communicating the status of your work clearly
• Present your work to the Data Science team, partner teams, and fellow interns

Who you are

Minimum requirements

We’re looking for someone who has:

• Enrolled in a quantitative PhD program (e.g. Data Science, Statistics, Economics, Mathematics, etc.) with the expectation of graduating in winter 2026 or spring/summer 2027
• Experience with a scientific computing language (such as Python, R, etc) and SQL. We believe new programming languages can be learned if the fundamentals and general knowledge are present!
• Knowledge and hands-on experience in several of the following areas: machine learning, statistics, optimization, product analytics, causal inference, and/or experimentation
• Experience communicating and collaborating with multidisciplinary stakeholders in a team environment

Preferred qualifications

You also likely have:

• Experience writing and debugging data pipelines
• Demonstrated ability to evaluate and receive feedback from mentors, peers, and stakeholders via experience from previous internships or other multi-person projects
• Ability to learn new systems and form an understanding of those systems, through independent research and working with a mentor and subject matter experts

About the Team

Stitch Fix is redefining retail by blending the art of fashion with the science of machine learning. Throughout the company's history, the Client Experience Algorithms Organization has been a key source of our innovation and competitive differentiation. We build the tools that power personal style, combining best-in-class models with expert human judgment. We foster a culture of ownership where Data Scientists manage the full lifecycle of their work, from research to model deployment. You’ll use multidisciplinary tools to solve complex problems in a data-rich environment, directly influencing how millions of clients discover what they love.

The Recommendation Algorithms team is building the future of personalized apparel shopping by thoughtfully combining algorithms with product innovation. A key area of focus is the continued improvement of the quality of recommended assortments along various dimensions, including seasonality, diversity, and freshness. A secondary area is the ability to deliver high-quality recommendations in real time to engage and delight new clients and therefore expand our total addressable market 

About the Role

This role will lead the development of our outfit completion models. These models combine client preferences, stylist expertise, and machine learning to inspire and guide client discovery through personalized and cohesive outfits.

A key area of focus is improving the quality and relevance of generated outfits across dimensions such as cohesiveness, diversity, and contextual awareness (e.g., occasion, seasonality, and trendiness). This role will also drive innovation in how these models are trained, evaluated, and served in real-time, ensuring a seamless and engaging client experience.

You're excited about this opportunity because you will…

• Lead the technical direction and development of our outfit completion models, a critical component of the Stitch Fix client experience
• Drive end-to-end model development, from problem formulation and research to production deployment and iteration
• Design and implement state-of-the-art machine learning models (including deep learning approaches in PyTorch) to model relationships between items and generate high-quality outfits
• Mentor and guide other data scientists on the team, raising the bar for modeling, experimentation, and engineering excellence
• Own and evolve experimentation strategies, defining success metrics and translating results into clear business impact
• Partner cross-functionally with Product, Engineering, and Design to shape the roadmap for outfit-based experiences across StitchFix.com
• Tackle ambiguous, high-impact problems and bring structure, clarity, and technical leadership to drive solutions forward
• Leverage rich, multi-modal datasets spanning client behavior, merchandise attributes, and stylist inputs to power innovative recommendations

We’re excited about you because…

• You have 5+ years of experience building and deploying machine learning models, including deep learning models in frameworks such as PyTorch
• You have strong experience with recommendation systems, ranking, or related domains (e.g., retrieval, embeddings, or generative modeling)
• You have demonstrated technical leadership, including mentoring other ICs, leading projects, or setting modeling direction
• You are comfortable owning ambiguous problem spaces and driving projects from concept to production
• You have deep experience with experimentation and causal inference, and can connect model improvements to business outcomes
• You are fluent in SQL and experienced working with large-scale datasets
• You are proficient in Python and have experience building production-ready data science systems
• You are an effective communicator who can influence cross-functional partners and align teams around a shared vision
• You are curious, pragmatic, and motivated to continuously raise the bar for both yourself and your team

Why you'll love working at Stitch Fix...

• We are a group of bright, kind people who are motivated by challenge. We value integrity, innovation and trust. You’ll bring these characteristics to life in everything you do at Stitch Fix.
• We cultivate a community of diverse perspectives— all voices are heard and valued.
• We are an innovative company and leverage our strengths in fashion and tech to disrupt the future of retail. 
• We win as a team, commit to our work, and celebrate grit together because we value strong relationships.
• We boldly create the future while keeping equity and sustainability at the center of all that we do. 
• We are the owners of our work and are energized by solving problems through a growth mindset lens. We think broadly and creatively through every situation to create meaningful impact.
• We offer comprehensive compensation packages and inclusive health and wellness benefits.