About the Team

The Discovery team is organized around the north star of building an AI scientist — a system capable of solving the long-horizon reasoning challenges and core capabilities needed to push the scientific frontier. The team trains large-scale models, runs complex multi-week experiments, and builds novel products at the intersection of AI and science.

About the Role

As a Technical Program Manager on the Discovery team, you will own the systems and programs that determine how fast our research moves: compute planning, scientific RL environment health, and the vendor pipelines that supply them, with scope to incubate new programs in domains like bio R&D. Strong candidates should have an ML engineering or research background and have grown into program leadership. You'll need real technical depth: the ability to debug data pipelines, read RL transcripts to spot issues, and make allocation and quality decisions in real time when experimental or production runs hit problems. You'll need organizational effectiveness in equal measure: the ability to navigate a fast-growing organization, quickly identify the critical people and teams across research, infrastructure, product, and data operations, and coordinate across them without losing velocity.

Join us in our mission to build AI systems that push the frontiers of science and benefit humanity.

Responsibilities

• Manage Discovery's compute planning across supervised learning (SL), reinforcement learning (RL), and sandboxing workloads, including forecasting, allocation, prioritization, and efficiency improvements. Partner with central compute planning to ensure Discovery's needs are represented and met.
• Monitor the health of scientific RL environments (quality, reward integrity, failure rates) and drive issues to resolution.
• Expedite the external vendor pipeline for RL environments, including quality review, reward design, and production integration.
• Work with research teams across life sciences, STEM, and other scientific domains to translate research goals into roadmaps that advance AI scientist capabilities.
• Establish processes and frameworks that bring structure to an unstructured research setting without slowing researchers down.
• Collaborate with research leads, infrastructure engineers, and data operations to identify blockers, prioritize competing needs, and make technical trade-off decisions.

You May Be a Good Fit If You:

• Have a background in ML engineering, ML research, or STEM R&D before transitioning to technical program management
• Have deep, hands-on experience with ML training pipelines, RLHF systems, and large-scale data infrastructure in production.
• Have a track record of building execution plans and inventing high-leverage processes that reduce operational overhead and let researchers focus on research.
• Are a fast learner who builds deep contextual understanding in unfamiliar technical domains and can contribute meaningfully to discussions with researchers.
• Are resourceful, high-agency, and able to navigate ambiguity and shifting priorities to drive progress in a fast-moving research setting
• Have excellent stakeholder management and communication skills, with the ability to influence senior technical staff through clarity, competence, and consistent delivery.
• Are excited about the potential for AI to accelerate scientific discovery

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.

What you’ll do

Responsibilities

• Apply statistical, time series forecasting and machine learning models on large datasets to predict future performance of users or products.
• Partner closely with Sales and Data Science teams to identify important questions and answer them with data. 
• Design, implement and launch data science solutions using Python and R to empower data-driven decisions and products at scale. 
• Create analyses that generate insights for business teams.
• Design, analyze, and interpret the results of experiments. 
• Build ETL data transformation pipelines in SQL.

Who you are

Minimum requirements

Must have a Master's degree or foreign equivalent in Computer Science, Business Analytics, Statistics, or a related quantitative field, plus 3 years of experience in a Data Scientist or related occupation. 

• 3 years of experience building ETL data transformation pipelines in SQL;
• 3 years of experience working closely with product and business teams to identify important questions and answer them with data;
• 2 years of experience productionalizing and implementing machine learning models;
• 2 years of experience productionalizing and implementing software products;
• 2 years of experience designing, analyzing, and interpreting the results of experiments;
• 2 years of experience designing, and analyzing software architectures;
• 2 years of experience designing, implementing, and launching data science solutions;
• 2 years of experience designing, implementing, and launching software solutions; and
• 2 years of experience applying statistical and machine learning models on large datasets to predict future performance of users or products.

Salary : $192,000 - $288,000/yr.

This salary range represents the base salary range for the role and any sales commissions/sales bonuses targets, if applicable, would be in addition to the base salary.

40 hrs/week

50% Telecommuting Permitted.

Multiple Positions Available.

Additional benefits for this role may include: equity, company bonus or sales commissions/bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends. WA04 #LI-DNI

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As a Staff Machine Learning Research Scientist on the LLM Evals team, you will lead the development of novel evaluation methodologies, metrics, and benchmarks to measure the capabilities and limitations of frontier LLMs. You will help define what "good" looks like in generative AI, driving research that informs both our internal roadmap and the broader research community. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs.

You will:

• Drive research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Mentor and guide research scientists and engineers, providing technical leadership across cross-functional projects.
• Stay deeply engaged with the ML research community, tracking emerging work and contributing to the advancement of LLM evaluation science.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience tech leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities.

In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models.

You will:

• Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities.
• Design and experiment new approaches to preference optimization.
• Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
• Publish research findings in top-tier AI conferences.

Ideally you’d have:

• Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field.
• Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
• Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
• Excellent written and verbal communication skills

• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, fueling the most exciting advancements in AI, including generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re amplifying access to high-quality data to drive progress toward Artificial General Intelligence (AGI). Building on our history of model evaluation with enterprise and government customers, we are expanding our capabilities to set new standards for both public and private evaluations.

About This Role

This role operates at the forefront of AI research and real-world implementation, with a strong focus on reasoning within large language models (LLMs). The ideal candidate will study the data types critical for advancing LLM-based agents, including browser and software engineering (SWE) agents. You will play a key role in shaping Scale’s data strategy by identifying the most effective data sources and methodologies for improving LLM reasoning. Success in this role requires a deep understanding of LLMs, planning algorithms, and novel approaches to agentic reasoning, as well as creativity in tackling challenges related to data generation, model interaction, and evaluation. You will contribute to impactful research on language model reasoning, collaborate with external researchers, and work closely with engineering teams to bring state-of-the-art advancements into scalable, real-world solutions.

Ideally, you’d have:

• Practical experience working with LLMs, with proficiency in frameworks like PyTorch, JAX, or TensorFlow. You should also be skilled at rapidly interpreting research literature and turning new ideas into working prototypes.

• A track record of published research in top ML and NLP venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, CoLLM, etc.).

• At least three years of experience solving complex ML challenges, either in a research setting or product development, particularly in areas related to LLM capabilities and reasoning.

• Strong written and verbal communication skills, along with the ability to work effectively across teams.

Nice to have:

• Hands-on experience fine-tuning open-source LLMs or leading bespoke LLM fine-tuning projects using PyTorch/JAX.

• Research and practical experience in building applications and evaluations related to LLM-based agents, including tool-use, text-to-SQL, browser agents, coding agents, and GUI agents.

• Experience with agent frameworks such as OpenHands, Swarm, LangGraph, or similar.

• Familiarity with advanced agentic reasoning techniques such as STaR and PLANSEARCH.

• Proficiency in cloud-based ML development, with experience in AWS or GCP environments.

Our research interviews are designed to assess candidates' ability to prototype and debug ML models, their depth of understanding in research concepts, and their alignment with our organizational culture. We do not conduct LeetCode-style problem-solving assessments.

Scale AI accelerates the development of AI systems by providing the data, infrastructure, and tooling that power the most advanced models in the world. Our teams operate at the intersection of cutting-edge research, large-scale engineering, and real-world deployment, partnering with leading frontier labs, enterprises, and government agencies to push Generative AI into new capabilities and applications.

As AI rapidly evolves from static models to dynamic, agentic systems, Scale is building the foundational research, evaluation methodologies, and agent/RL infrastructure that will define this next era. You’ll join a high-impact research organization driving advances in large-language models, post-training, evaluation, and agentic/RL environments, helping shape how next-generation AI is built, measured, and deployed.

As a Research Scientist Manager, you will lead a world-class team of research scientists and engineers, define the research roadmap, and drive execution from early prototyping to deployment. You’ll thrive in a fast-moving environment, balancing deep technical leadership with people management, vision setting, and delivery.

You will:

• Lead, mentor and grow a team of research scientists and engineers working on GenAI research initiatives (e.g., evaluation, post-training, agents, RL environments).  
• Define and drive a multi-year research roadmap: identify key scientific questions, set milestones, allocate resources, and ensure rigorous execution.
• Collaborate cross-functionally with engineering, product, client-facing teams and external academic or industry partners to translate research into components, insights, and actionable outcomes.
• Communicate compellingly: publish research, present at conferences, engage in open-source contributions, and represent the team externally.
• Drive an inclusive, high-performing culture: help your team through technical challenges, provide growth opportunities, and attract top talent.
• Stay deeply connected to the research community, understanding major trends, and helping set them.
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on research experience (PhD or equivalent preferred) in machine learning, deep learning, generative models, agent/rl systems or related domains.
• A strong track record of research excellence, including publications in top-tier ML/AI venues (NeurIPS, ICML, ICLR, ACL, etc.).
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience leading or managing research teams. You’re excited to mentor, coach and develop talent.
• Excellent written and verbal communication skills. You are able to articulate research ideas and outcomes to both technical and non-technical stakeholders.

About Scale

At Scale AI, our mission is to accelerate the development of AI applications. For 8 years, Scale has been the leading AI data foundry, helping fuel the most exciting advancements in AI, including: generative AI, defense applications, and autonomous vehicles. With our recent Series F round, we’re accelerating the abundance of frontier data to pave the road to Artificial General Intelligence (AGI), and building upon our prior model evaluation work with enterprise customers and governments, to deepen our capabilities and offerings for both public and private evaluations.

About the ACE team 

The Agent Capabilities & Environments (ACE) team, part of Scale’s Research organization, brings together customer-facing Researchers and Applied AI Engineers. Our core mission includes research on agent environments and RL reward signals, benchmarking autonomous agent performance across real-world scenarios and environments, creating robust data programs to improve Large Language Models (LLMs) agentic capabilities and building foundational tools and frameworks for evaluating models as agents. ACE focuses on autonomous agents that dynamically interact with diverse external environments, including code repositories, GUI interfaces, browsers, and more. 

About This Role

This role is at the intersection of cutting-edge AI research and practical application, with a focus on studying the data types essential for building state-of-the-art agents, such as browser and SWE agents. The ideal candidate will explore the data landscape needed to advance intelligent, adaptable AI agents, guiding the data strategy at Scale to drive innovation. This position requires not only expertise in LLM agents and planning algorithms but also creativity in addressing novel challenges related to data, interaction, and evaluation. You will contribute to impactful research publications on agents, collaborate with customer researchers, and work alongside the engineering team to translate these advancements into real-world, scalable solutions.

Ideally you’d have: 

• Practical experience working with LLMs, with proficiency in frameworks like Pytorch, Jax, or Tensorflow. You should also be adept at interpreting research literature and quickly turning new ideas into prototypes.
• A track record of published research in top ML venues (e.g., ACL, EMNLP, NAACL, NeurIPS, ICML, ICLR, COLM, etc.)
• At least three years of experience addressing sophisticated ML problems, either in a research setting or product development.
• Strong written and verbal communication skills and the ability to operate cross-functionally. 

Nice to have:

• Hands-on experience with open source LLM fine-tuning or involvement in bespoke LLM fine-tuning projects using Pytorch/Jax. 
• Hands-on experience and publications in building applications and evaluations related to AI agents such as tool-use, text2SQL, browser agents, coding agents and GUI agents.
• Hands-on experience with agent frameworks such as OpenHands, Swarm, LangGraph, etc.
• Familiarity with agentic reasoning methods such as STaR and PLANSEARCH 
• Experience working with cloud technology stack (eg. AWS or GCP) and developing machine learning models in a cloud environment.

Our research interviews are crafted to assess candidates' skills in practical ML prototyping and debugging, their grasp of research concepts, and their alignment with our organizational culture. We will not ask any LeetCode-style questions.

As the leading data and evaluation partner for frontier AI companies, Scale is dedicated to advancing the evaluation and benchmarking of large language models (LLMs). We are building industry-leading LLM evals, setting new standards for model performance assessment. Our mission is to develop rigorous, scalable, and fair evaluation methodologies to drive the next generation of AI capabilities.

Our Research teams work with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. As the Tech Lead Manager of the LLM Evals Research team, you will lead a talented team of research scientists and research engineers focused on developing and implementing novel evaluation methodologies, metrics, and benchmarks to assess the capabilities and limitations of our cutting-edge LLMs. This role is critical for designing and executing a roadmap that defines best practices in data driven AI development and will accelerate the next generation of generative AI models in partnership with top foundational model labs. 

You will:

• Lead a team of highly effective research scientists and research engineers on LLM evals.
• Conduct research on the effectiveness and limitations of existing LLM evaluation techniques.
• Design and develop novel evaluation benchmarks for large language models, covering areas such as instruction following, factuality, robustness, and fairness. 
• Communicate, collaborate, and build relationships with clients and peer teams to facilitate cross-functional projects.
• Collaborate with internal teams and external partners to refine metrics and create standardized evaluation protocols.
• Implement scalable and reproducible evaluation pipelines using modern ML frameworks.
• Publish research findings in top-tier AI conferences and contribute to open-source benchmarking initiatives.
• Remain up-to-date on ongoing research in the team, help work through technical challenges, and be involved in design decisions
• Remain deeply involved in the research community, both understanding trends, and setting them
• Thrive in a high-energy, fast-paced startup environment and are ready to dedicate the time and effort needed to drive impactful results.

Ideally you'd have:

• 5+ years of hands-on experience in large language model, NLP, and Transformer modeling, in the setting of both research and engineering development
• Experience and track of recording in landing major research impacts in a fast-paced environment
• Experience supporting and leading a team of research scientists and research engineers
• Excellent written and verbal communication skills
• Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals
• Previous experience in a customer facing role.

Location Details: 

At GoDaddy the future of work looks different for each team. Some teams work in the office full-time, others have a hybrid arrangement (they work remotely some days and in the office some days) and some work entirely remotely.

This is a remote position, so you’ll be working remotely from your home. You may occasionally visit a GoDaddy office to meet with your team for events or meetings.  

This position is not eligible to be performed in Alaska, Mississippi, North Dakota, or the Virgin Islands.

We encourage you to apply even if your experience or skillset doesn’t align perfectly with every requirement. We value a wide range of backgrounds and transferable skills, and we are excited to support learning and growth.

About us...  GoDaddy is empowering everyday entrepreneurs around the world by providing the help and tools to succeed online, making opportunity more inclusive for all. GoDaddy is the place people come to name their idea, build a professional website, attract customers, sell their products and services, and manage their work. Our mission is to give our customers the tools, insights, and people to transform their ideas and personal initiative into success. To learn more about the company, visit About Us. 

At GoDaddy, we know diverse teams build better products—period. Our people and culture reflect and celebrate that sense of diversity and inclusion in ideas, experiences and perspectives. But we also know that’s not enough to build true equity and belonging in our communities. That’s why we prioritize integrating diversity, equity, inclusion and belonging principles into the core of how we work every day—focusing not only on our employee experience, but also our customer experience and operations. It’s the best way to serve our mission of empowering entrepreneurs everywhere, and making opportunity more inclusive for all. To read more about these commitments, as well as our representation and pay equity data, check out our Diversity and Pay Parity annual report which can be found on our Diversity Careers page.

We also embrace our diverse culture and offer a range of Employee Resource Groups (Culture). Have a side hustle? No problem. We love entrepreneurs! Most importantly, come as you are and make your own way. 

GoDaddy is proud to be an equal opportunity employer. GoDaddy will consider for employment qualified applicants with criminal histories in a manner consistent with local and federal requirements. Refer to our full EEO policy.

Our recruiting team is available to assist you in completing your application. If they could be helpful, please reach out to myrecruiter@godaddy.com. 

Colorado Residents: In any materials you submit, you may redact or remove age-identifying information such as age, date of birth, or dates of school attendance or graduation. You will not be penalized for redacting or removing this information.

GoDaddy doesn’t accept unsolicited resumes from recruiters or employment agencies.

About the Role

The impact you'll be contributing to Moloco:
The Research Science (RS) team focuses on the operation and optimization of our software systems working closely with infrastructure engineering teams, machine learning teams and data science teams. As an Applied Scientist, you will participate as an individual contributor on research projects alongside other research scientists within the context of a group of cross functional collaborators working in complex multi-causal environments to identify inefficiencies, analyze potential options, and propose solutions. Your work will contribute to driving performance improvements and cost reductions, debugging and investigating production issues, and stabilizing our core system as you develop a deep end-to-end understanding of the system.

Here’s what you’ll be working on:

• Work with other applied scientists on projects to evaluate the health of both internal and external components to make sure the Moloco system is running safely and efficiently.  
• Learn from your senior peers how to identify new areas to improve our infrastructure and machine learning components by understanding internal system changes, external changes, and data changes, and identify and suggest interesting/useful next steps for your projects.
• Complete task as part of larger projects to complete deep unbiased analyses.  
• Implement, and evaluate new algorithms and features in collaboration with senior Applied Scientists, Software Engineers and Machine Learning Engineers.

Basic Qualifications:

• Advanced degree in Computer Science, Mathematics or related field, or industry experience in optimization of market prices or ML systems
• At least 4 years of engineering or applied science experience
• Proficient verbal and written English communication skills, with the ability to contribute to the creation of presentations and reports
• Quick understanding of new information and the demonstrated ability to learn new technical skills across engineering, machine learning, and data science 
• Track record of building positive relationships with collaborators and stakeholders and working effectively with cross-functional partners in a global company

The impact you'll be contributing to Moloco:

Creatives are one of the highest-leverage levers in Moloco Ads: they shape what users see, how they interact, and ultimately how much value advertisers extract from our platform. As formats grow more complex (video, playables, rich HTML) and surfaces diversify across exchanges, SDK, and new inventory types, our creative systems must do more than just serve assets — they must learn, adapt, and guide advertisers toward better outcomes.

This space sits at the intersection of ML/bidding, supply, and UI/UX for advertisers. Strong product decisions here directly influence company toplines, ROAS and advertiser retention. At the same time, weak creative strategy can quietly erode performance, create operational noise, and diminish trust in our optimization systems. We need a Staff Product Data Scientist who can bring structure, rigor, and long-term thinking to this inherently noisy problem space.

The person will be the analytical and product thought partner for the Creatives team, owning the data narrative across ideation, launch, and iteration of creative features and strategies. This is not a “support” role; it is a co-owner of the creative roadmap.

Here’s what you’ll be working on:

This role is critical to ensuring that Moloco’s creative systems become a long-term competitive advantage, not just a collection of formats and features.

• Be recognized as a thought leader in the creative domain, someone whose perspective is actively sought when making high-stakes product calls. For example, influence which creative problems we choose to solve, not just how we measure the outcomes.
• Establish a trusted, repeatable framework for measuring creative impact that the organization rallies around. This will enable PM/ENG to ship creative features faster and with more confidence, backed by well-designed experiments and clear success criteria.
• Reduce ad-hoc fire drills by building durable monitoring, diagnostics, and documentation that make creative performance and adoption more transparent.

Minimum Qualifications

• Bachelor’s degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Physics) or equivalent practical experience.
• 8+ years of experience (or PhD + 6 YoE) in data science, product analytics, or a closely related quantitative field, including significant time as a product-facing IC.
• Proven track record of partnering with Product and Engineering to shape roadmaps, define success metrics, and drive decisions through data.
• Demonstrated ability to operate with high ownership and autonomy, including scoping ambiguous problems and driving them to closure.
• Comfort working across time zones and with distributed teams, using strong async communication and documentation habits.

Preferred Qualifications

• Graduate or PhD degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Physics) or equivalent practical experience with 10+ years of experience in related fields. 
• Prior experience in ad tech, marketing science, or related domains where creatives, auctions, or optimization systems are central to performance.
• Hands-on experience with creative analytics (e.g., format benchmarking, asset-level performance analysis, interaction or engagement modeling).
• Experience collaborating closely with ML teams to design, evaluate, and iterate on model features and policies.
• Excellent communication skills: ability to synthesize complex analytical findings into simple, actionable narratives for technical and non-technical audiences.

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Staff Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

• This leader will own the multi-year strategy, roadmap, and execution across the ads supply ecosystem:
  • Supply Exchange & Inventory Integrations: Drive Moloco’s OpenRTB integrations with top-tier third-party supply partners and exchanges, expanding Moloco’s access to high-quality, global, multi-format inventory across gaming and non-gaming verticals.
  • Lead Moloco’s end-to-end General Supply strategy, including Exchange integrations, OpenRTB supply diversification, publisher onboarding, and supply ecosystem expansion.
  • Define, evangelize, and deliver a multi-year supply vision that improves supply quality, scalability, integration reliability, and long-term differentiation
• Conducting deep-dive analysis and experiments to influence product decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers.

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Preferred Qualifications:

• Advanced degree. PhD is highly desirable. 
• Deep expertise in the programmatic supply ecosystem, including ad exchanges, SSPs, OpenRTB protocols, auction mechanics, and cross-platform integration
• Demonstrated ability to drive cross-org alignment, influence senior stakeholders (Directors/VPs), and execute through large engineering teams
• Familiarity with publisher ad servers, targeting logic, and impression delivery workflows
• Deep knowledge of supply-side performance metrics such as fill rate, eCPM, latency, bid density, impression opportunities, and unique users—and how to optimize for them
• Hands-on experience with integrations and partner-facing APIs, including defining requirements for interoperability with DSPs, exchanges, ad networks, DMPs, and other adtech partners

The impact you'll be contributing to Moloco:
Product Analytics Data Science (PDS) is the data science team that works closely with the R&D team on our core Ads product. As a Senior Data Scientist, you will drive performance improvement in our product through a deep understanding of the ads ecosystem (supply, demand, bidding, fraud detection) and customer needs, and provide the data driven insight and scientific solutions.

Here’s what you’ll be working on:

Our team is responsible for:

• Conducting deep-dive analysis to influence R&D decisions and strategies: analyzing large datasets with queries and scripts, extracting valuable signals out of noise, and producing actionable insights into how we could improve Moloco’s complex ML and bidding system to drive outcomes for customers. 
• Evaluating ads integrity: understanding changes and drivers of our complex systems, diagnosing fraud claims and mitigating fraud escalations through a set of input/output metrics of each component.
• Building the right metrics to measure campaign health: improving campaign performance monitoring by establishing the right metric framework, and understanding cause-and-effect relationships across drivers

Basic Qualifications

• Distinctive problem-solving skills, ability to articulate product questions, pulling data from large datasets and using statistics to arrive at a recommendation; ability to manage multiple projects at the same time. 
• Proven ability to own complex projects end-to-end, even when you have to get creative: you do more than completing delegated tasks and always pay attention to detail to translate analysis results into business recommendations. 
• Excellent verbal and written communication skills, with ability to present information and analysis results effectively.
• Statistics: strong knowledge and experience in experimental design, hypothesis testing, and various statistical analysis techniques such as regression or linear models.
• Programming: experience with Python, R or other scripting language, and database language (e.g. SQL) or data manipulation (e.g. Pandas, Dplyr).
• Ability to build positive relationships within the DS team and with our stakeholders, and work effectively with cross-functional partners in a global company.
• 6+ years of work experience (industry or postgraduate) in data science related fields or an advanced degree such as Master’s or PhD in a quantitative discipline with 4+ years of experience.

Bachelor’s, Master’s and/or PhD in a quantitative discipline (e.g. Statistics, Operations Research, Economics, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering).

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 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).

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.

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 New York City 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.

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 Seattle 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.

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 Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

We are looking for a highly strategic and technically strong Staff Data Scientist to join the Member Data Science team, focused on driving engagement and long-term member value, specifically for our subscription premium program, SoFi Plus. This role will be responsible for deeply understanding the drivers of engagement, retention, and subscription value across the SoFi ecosystem. You will define and own engagement measurement frameworks, lead high-impact analytical deep dives, design causal experiments, and develop scalable data and modeling solutions that inform product strategy for SoFi Plus. 

The Member Organization builds engaging and personalized experiences for our members across our product lines. As a Staff Data Scientist, you will operate as a data thought partner to Product, Engineering, Lifecycle Marketing, and Leadership. You will shape the engagement roadmap through insights on activation, feature adoption, habit formation, churn risk, subscription upgrades/downgrades, and long-term member value. You will proactively identify the most impactful opportunities to improve subscription engagement and revenue, and ensure we are making disciplined, data-informed investment decisions.  This role requires strong technical skills (SQL, Python/R, Tableau, Statistics), deep expertise in metrics, segmentation, A/B testing, and strong collaboration.

This is a highly cross-functional and high-visibility role with direct impact on member experience and recurring revenue growth. This is an exciting role for someone to make a direct impact on the company's growth trajectory and member experience.

Responsibilities:

• Design and implement data collection and processing pipelines
• Develop and apply machine learning models to solve business problems. Translate modeling outputs into actionable business strategies.
• Strong experience owning product analytics workflows including formulating success metrics, socializing them across the organization, and creating dashboards/reports
• Evaluate and interpret the results of data analysis
• Communicate findings to influence technical and non-technical stakeholders
• Stay up-to-date on the latest data science techniques and technologies
• Build data pipelines to deploy production level datasets
• Proven experience building scalable dashboards and executive-ready reports that measure product performance, subscription health, and engagement KPIs, and effectively translate insights into actionable business recommendations.
• Experience with leveraging LLMs or other AI solutions to develop analytical tools.

Qualifications:

• Master’s degree or higher in Statistics, Economics, Applied Mathematics, Computer Science, Engineering, or related quantitative field.
• 7+ years of experience leveraging data-driven analysis to influence product and business strategy, ideally in a tech or subscription-based company.
• Deep expertise in:
• Retention and engagement analytics
• Cohort and lifecycle analysis
• Subscription metrics (churn, LTV, ARPU)
• Experimental design and causal inference
• Strong proficiency in SQL, experience with visualization tools (e.g., Tableau) and python.
• Experience building data pipelines using DBT and orchestrating workflows with Airflow in Snowflake environments.
• Proven experience developing and deploying machine learning models in production with monitoring frameworks.
• Strong understanding of subscription economics and revenue optimization.
• Demonstrated ability to work independently in ambiguous environments and drive measurable business impact.
• Excellent communication skills, including the ability to present complex technical findings to executive audiences.
• Track record of mentoring junior data scientists and elevating team standards.

We’re looking for a highly skilled Senior Data Scientist to play a pivotal role on the Member Data Science team, focused on driving and accelerating member growth across a broad set of member growth initiatives. This role will be instrumental in establishing measurement frameworks and analytical infrastructure to support growth strategies end to end. Key responsibilities include defining success metrics, building tracking systems, designing experiments, conducting customer segmentation and price elasticity analyses, and optimizing member acquisition economics with propensity models. The Member Organization builds engaging and personalized experiences for our members across our product lines.

As a Sr. Data Scientist on the Member Growth pillar, you will be responsible for defining and owning core growth KPIs, building and maintaining reliable dashboards and reporting to track performance, and establishing clear success metrics across the growth funnel. You will conduct deep-dive analyses such as customer segmentation, funnel analysis, A/B testing, and elasticity or trade-off evaluations to identify levers that optimize conversion, and become an SME in our member referral program. You will develop models (e.g., propensity or uplift models) to inform targeting, prioritization, and investment decisions across growth initiatives. This role requires strong technical skills (SQL, Python/R, Tableau, Statistics), deep expertise in metrics, segmentation, experimentation, and strong collaboration.

This role is inherently cross-functional, you will work closely with engineering, product managers, lifecycle marketing, data science, design, operations, finance, and executive teams to set growth objectives, define referral program strategy, prioritize features, provide insights, and execute on them. This is an exciting role for someone to make a direct impact on the company's growth trajectory and member experience.

Responsibilities:

• Design and implement data collection and processing pipelines

• Develop and apply machine learning models to solve business problems

• Strong experience owning product analytics workflows including formulating success metrics, socializing them across the organization, and creating dashboards/reports

• Evaluate and interpret the results of data analysis

• Communicate findings to influence technical and non-technical stakeholders

• Stay up-to-date on the latest data science techniques and technologies

• Build data pipelines to deploy production level datasets

Qualifications:

• Bachelor’s degree required (Master’s preferred) in Computer Science, Math, Physics, Engineering or quantitative field. 

• 4+ years of relevant work experience 

• Strong programming skills in SQL, Python/R and proficiency in Tableau

• Proven experience creating dashboards and reports that drive business decisions

• Experience with using DBT, Airflow to build Data Pipelines in Snowflake

• Experience with experimental design/interpretation, A/B testing, quasi-experimentation for causal inference

• Experience with data mining, descriptive analytics, defining KPIs, machine learning, statistical modeling, and predictive modeling concepts.

• Experience with funnel analysis, cohort analysis, and segmentation

• Demonstrate strong business acumen and curiosity, with excellent communication and presentation skills, including the ability to present to leadership.

• Ability to work independently and as part of a team. You should be able to initiate and drive projects to completion 

• Exceptional problem-solving skills

• Influence outcomes and communicate technical content to general audiences 

• Work independently in a dynamic, cross-functional environment, with strong attention to detail and the ability to be a team player.

• Prepare comprehensive data reports and make insights easy to understand.

About the Role

We’re looking for an Applied Scientist (ALL LEVELS) to push the boundaries of applied machine learning and AI at Opendoor. While this role will have a significant impact on our valuation systems — ensuring we provide the most accurate and transparent pricing possible — the scope goes well beyond pricing. You’ll work across a range of challenging ML problems, from multi-modal modeling to operational optimization, helping us rethink how we use structured and unstructured data to make better decisions for our customers.

What You'll Need

• Strong software engineering and coding skills in Python, with experience contributing to production codebases
  
  
• Experience developing and deploying ML models end-to-end — from research and prototyping to implementation in production systems
  
  
• Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar
  
  
• Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field
  
  
• Solid foundation in statistics and experimental design
  
  
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly
  
  

Nice to Have

• Familiarity with Pyspark and distributed data processing
  
  
• Background in search, recommendation systems, or personalization
  
  
• Experience working with large language models (LLMs) or vision-language models (VLMs)
  
  
• A genuine interest in real estate — no prior experience required, but you'll engage deeply with housing data
  
  

What You'll Do

• Design and deploy architectural improvements to our deep neural network (DNN)-based home valuation models
  
  
• Build interpretable ML models that can help us explain pricing decisions to customers
  
  
• Incorporate unstructured data — like images, videos, or text — into our forecasting and valuation pipelines using cutting-edge AI models (LLMs, VLMs, etc.)
  
  
• Collaborate with Engineering and Ops to enhance our human-in-the-loop pricing systems
  
  
• Improve the feature engineering and model training pipelines that power our production systems
  
  
• Rethink our risk and optimization models using real-world data and domain insight
  
  

We’re a small, nimble team — there’s ample opportunity to work across the entire research and modeling stack.

Compensation

The base pay range for this position is $156,800-$310,000 annually, plus RSUs. Pay within this range varies by work location and may also depend on your qualifications, job-related knowledge, skills, and experience. We also offer a comprehensive package of benefits including unlimited PTO, medical/dental/vision insurance, life insurance, and 401(k) to eligible employees.

#LI-RO

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

About the Role

What You'll Need

• Experience developing quantitative models to support real-world decision-making under uncertainty
• Strong coding skills in Python, with the ability to move beyond prototyping and implement production-quality scientific code
• Experience with one or more of the following: causal inference, Bayesian modeling, structural modeling, demand forecasting, pricing science, or mathematical optimization
• Comfort working with messy, high-dimensional real-world data and translating ambiguous business problems into rigorous modeling approaches
• Advanced degree (MS or PhD preferred) in statistics, mathematics, economics, operations research, computer science, or another quantitative discipline
• Strong communication and collaboration skills — you’re comfortable working with cross-functional stakeholders and can communicate technical ideas clearly

Nice to Have

What You'll Do

Compensation

We are looking for Data Scientists to join our Monetization Engineering organization. You will take end to end ownership of designing, researching, building, and delivering data products as well as collaborate with XFNs to formulate, experiment, and evolve Pinterest’s strategy in the Ads space.

What you’ll do:

• Deep strategic analysis to answer core questions such as: How do we assess the trade-off between metrics change? How should we evaluate overall impact from changes in one component of the ads ecosystem?
• Opportunity sizing and analysis. Should Pinterest adjust programmatic ad load based on ? Write clear, actionable analyses that help teams identify areas of improvement and investment.
• Modeling: Build segmentation models to assess supply to inform pricing strategy.
• Improve decision velocity and quality using data scientist tool kit: experimentation, causal inference techniques, etc. Design measurement strategy, advise on experimentation best practices, identifying flaws in experiment practices and results; building tools for experiment analysis etc.
• Creating and tracking success metrics. Identify the right measures of success for engineering teams and help them track those metrics. Break down high-level metrics into actionable segments. This work may span from collecting entirely new datasets to building dashboards to track components of a metric (e.g., monitoring conversion data for missing values, implausible values, duplicated data, etc. by advertiser over time).
• Leadership: Lead and mentor the scope of work for data scientists in the same area, demonstrating high-quality output of both yourself and others for whom you are responsible. Provide continuous and candid feedback, recognizing individual strengths and contributions and flagging opportunities to improve performance.

What we’re looking for:

• Bachelor’s/Master’s degree in a relevant field such as Data Science, or equivalent experience
• 5+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data.
• Strong fundamentals in statistics, experimentation.
• Domain knowledge in ecosystem, ads, or real-time-bidding.
• Proven ability to apply scientific methods to solve real-world problems on web-scale data.
• Proficiency in SQL/Hive/Python.

Relocation Statement:

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

#LI-HYBRID

#LI-JT6

Apex is expanding its environmental leadership team in the Seattle Metro area, and we’re seeking an accomplished Professional Engineer or Geologist to spearhead the continued growth of our regional environmental practice. This is an exciting opportunity to grow a thriving environmental consulting practice that serves some of the most dynamic clients and complex sites in the Puget Sound region.

What You’ll Do:

• Lead and grow Apex’s regional environmental consulting practice, with a focus on site characterization, investigation, and remediation of upland and waterfront sites.
• Develop and maintain trusted client relationships, serving as a strategic advisor to both long-term partners and new business opportunities.
• Direct high-visibility projects, ensuring technical excellence, regulatory compliance, and successful environmental outcomes.
• Collaborate and communicate effectively on key technical concepts to regulators, stakeholders, and teaming partners.
• Drive growth and profitability across the practice.

Qualifications:

• 15+ years of environmental consulting experience with progressive responsibility and leadership.
• Professional registration as a PE or PG in Washington State.
• Proven success in business development, client engagement, and managing complex environmental programs.
• Deep experience with site characterization, investigation, remediation, and regulatory strategy.
• Strong communication skills — both technical and strategic — with a proven ability to connect with regulators, stakeholders, and clients.
• A passion for mentoring, leadership, and advancing a culture of excellence and safety.

Why Apex:

• 70+ team members in the Puget Sound region and 300+ team members in the Pacific Northwest
• Full service environmental and engineering delivery capacity
• 1,700+ employee national firm with 70+ locations across the US.
• Company-subsidized medical and dental.
• Company-paid life, short, and long-term disability.
•  401k match, tuition assistance, and more.
• Performance-based bonuses or other incentives.

Location: Seattle Metro Area

Salary: $150,000–$200,000+ annually (DOE)

Employment Type: Full-time with comprehensive benefits and performance-based incentives

Req ID: 10752

Apex is expanding its environmental leadership team in the Seattle Metro area, and we’re seeking an accomplished Professional Engineer or Geologist to spearhead the continued growth of our regional environmental practice. This is an exciting opportunity to grow a thriving environmental consulting practice that serves some of the most dynamic clients and complex sites in the Puget Sound region.

What You’ll Do:

• Lead and grow Apex’s regional environmental consulting practice, with a focus on site characterization, investigation, and remediation of upland and waterfront sites.
• Develop and maintain trusted client relationships, serving as a strategic advisor to both long-term partners and new business opportunities.
• Direct high-visibility projects, ensuring technical excellence, regulatory compliance, and successful environmental outcomes.
• Collaborate and communicate effectively on key technical concepts to regulators, stakeholders, and teaming partners.
• Drive growth and profitability across the practice.

Qualifications:

• 15+ years of environmental consulting experience with progressive responsibility and leadership.
• Professional registration as a PE or PG in Washington State.
• Proven success in business development, client engagement, and managing complex environmental programs.
• Deep experience with site characterization, investigation, remediation, and regulatory strategy.
• Strong communication skills — both technical and strategic — with a proven ability to connect with regulators, stakeholders, and clients.
• A passion for mentoring, leadership, and advancing a culture of excellence and safety.

Why Apex:

• 70+ team members in the Puget Sound region and 300+ team members in the Pacific Northwest
• Full service environmental and engineering delivery capacity
• 1,700+ employee national firm with 70+ locations across the US.
• Company-subsidized medical and dental.
• Company-paid life, short, and long-term disability.
•  401k match, tuition assistance, and more.
• Performance-based bonuses or other incentives.

Location: Seattle Metro Area

Salary: $150,000–$200,000+ annually (DOE)

Employment Type: Full-time with comprehensive benefits and performance-based incentives

Req ID: 10752

Role Overview: 

We are seeking a Senior Ergonomist with industrial and applied ergonomics experience to support a handful of our key Apex clients. This is a part‑time, traveling role - with expense covered - ideal for an experienced professional who excels in practical, field-based ergonomics and enjoys working directly with operations, safety, engineering, facilities, labor, leadership and other stakeholders. 

The Senior Ergonomist will perform ergonomics assessments, collaboratively develop solutions and project manage solution implementation in industrial manufacturing and warehouse settings to reduce musculoskeletal injury risk while improving productivity and worker well‑being. 

Your Responsibilities as a Senior Ergonomist:

• Conduct on-site ergonomic assessments in industrial environments (e.g., manufacturing, warehousing, distribution, logistics, construction, utilities). 
• Identify, evaluate, and prioritize ergonomic risk factors related to manual material handling, repetitive tasks, awkward postures, vibration, and forceful exertions. 
• Develop practical, cost-effective ergonomic solutions, including engineering controls, administrative controls, and tool/equipment recommendations. 
• Collaborate with EHS, Operations, Engineering, and Maintenance teams to implement ergonomic improvements. 
• Apply published design standards on workstation design, equipment selection, process changes, and job/task design. 
• Support injury prevention efforts, including analysis of MSD trends, root cause investigations, and return-to-work accommodations. 
• Prepare concise technical reports, risk assessments, and recommendations either within our clients’ various reporting systems or as a standalone report.   
• Stay current on ergonomics standards, best practices, and regulatory expectations relevant to industrial work. 
• Support and maintain strong communications between our clients and our Apex leadership. 

What we're looking for:

Required Qualifications 

• Bachelor’s degree or higher in Ergonomics, Human Factors, Industrial Engineering, Occupational Health, or a related field. 
• 5–10+ years of professional ergonomics experience, with an emphasis on industrial settings. 
• Demonstrated expertise in:  
• Manual material handling analysis 
• Task and job hazard analysis 
• Ergonomic assessment tools (e.g., REBA, RULA, NIOSH Lifting Equation, Strain Index) 
• Proven ability to for project management resulting in implementation of solutions that objectively improve injury risk or process efficiency. 
• Strong communication skills with the ability to understand and influence front-line workers through senior leadership. 
• Willingness and ability to travel regularly (with per diem expenses covered for assignments) for a few days up to multi-week stays in various locations across the US. 
• Proficient in MS Office (Word, Excel, PowerPoint);  

Preferred Qualifications 

• Professional certification (e.g., CPE, CIE, CSP, CIH, PT, OT). 
• Experience working within EHS or injury prevention programs. 
• Familiarity with manufacturing processes, automation, heavy equipment, and material handling systems. 
• Experience supporting multi-site or enterprise-level ergonomics programs. 

Physical & Travel Requirements 

• Ability to walk industrial facilities, climb stairs/ladders, and observe physical work activities. 
• Ability to lift light equipment (e.g., measurement tools, laptops). 
• Willingness to travel frequently, including overnight stays. 

Job Location: 

Seattle / Puget Sound area is optimal, but remote support could be acceptable with travel (easy access to an airport is a must). 

Travel Expectations: 

Travel will be up to 75% with variation depending on stage of the project and need for on-site presence.  

Why you'll love working for us:

• Company-subsidized medical and dental.
• Company-paid life, short, and long-term disability.
• 401k match, tuition assistance, and more.
• Cross-training and the ability to work on a variety of projects.
• Performance-based bonuses or other incentives.
• Working with the best and brightest in the industry.
• 2,000+ employee national firm with 70+ locations across the US.

Req ID: 11497

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $167,030 - $260,570, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who You Are: 

Research Scientists in the Ai2 Robotics Team will have the unique opportunity to develop and investigate core research problems in foundation models for robotics, and contribute to the development of completely open methods, data sets, benchmarks, and models. They will experiment with large-scale simulation tools and robots in the real world.  

Research Scientists will work on multiple exciting research projects in the above areas but can also contribute and engage in a variety of other activities critical to our research and mission. These include opportunities to lead projects, mentor interns and pre-doctoral candidates, author and present scientific papers, and collaborate with researchers at other organizations including universities. 

At Ai2, you will be working with world-class AI and robotics researchers and talented software engineers. You will perform team-based, ambitious research, with a mandate to strive for big breakthroughs, not just incremental progress, in an exciting and interactive workplace.

Who We Are: 

Ai2’s Robotics team is led by Dieter Fox. We aim to develop and leverage scalable simulation domains to scientifically investigate the scaling and generalization capabilities of foundation models for robotics, and use these insights to develop broadly competent robots. Following a longstanding tradition at Ai2, we are committed to fully open-source research and work toward application domains with a positive impact on society. 

We are looking for applicants interested in robotics, with a focus on core techniques in robot manipulation, large scale training in simulated environments, sim-to-real transfer, robot foundation models, and skill learning. 

We regularly publish in high-profile conferences and journals in robotics (CoRL, ICRA, RSS), computer vision (CVPR, ICCV, ECCV), and machine learning (e.g., NeurIPS, ICLR, ICML). 

We collaborate frequently with researchers on other Ai2 teams focused on computer vision, large language models, and others. Our main office has close ties and unique access to researchers at the University of Washington, only 1.5 miles away. Researchers excited about such internal and external collaborations are encouraged to apply.

Your Next Challenge: 

At Ai2, you will be working with world-class AI researchers and talented software engineers. We perform team-based, ambitious research, with a mandate to strive for big breakthroughs, not just incremental progress, in an exciting and interactive workplace.  

All scientists have the opportunity to mentor interns (and other students)and will participate directly in Ai2's groundbreaking work. There are no restrictions on publications.  

What You’ll Need: 

• A strong foundation (typically PhD level) in one or more of the following areas: robot manipulation, planning and control, RL and imitation learning, real world robot systems, simulation environments and sim2real, and world models and foundation models.  
• A strong publication record in AI-related areas.  Example venues include CoRL, ICRA, RSS, CVPR, ICCV, ECCV, NeurIPS, ICLR, etc. Contributions to research communities (e.g. workshop organization, tutorials) are a plus. 
• Strong software engineering skills.  Experience working with real robot systems and/or with deep learning frameworks.  

• (Optional) Research experience in related areas like large-scale multi-node training, training dynamics, efficiency, data curation, and multimodal model debugging, post-training methods, among others. 
• (Optional) Contributions to open-source research libraries.

Physical Demands and Work Environment: 

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions. 

• Must be able to remain in a stationary position for long periods of time.  
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations.  
• The ability to observe details at close range. 
• Can work under deadlines. 

A Little More About Ai2: 

Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ (and growing) people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links.  

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9. 

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org  

Benefits:  

• Team members and their families are covered by medical, dental, vision, basic life insurance, basic accidental death and dismemberment insurance, short-term disability, long-term disability, and an employee assistance program.
• Team members are able to enroll in our voluntary life insurance program, our voluntary accidental death and dismemberment program, our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans.
• Team members are able to enroll in our company’s 401k plan.
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.

About impact.com
impact.com is the world’s leading commerce partnership marketing platform, transforming the way businesses grow by enabling them to discover, manage, and scale partnerships across the entire customer journey. From affiliates and influencers to content publishers, brand ambassadors, and customer advocates, impact.com empowers brands to drive trusted, performance-based growth through authentic relationships. Its award-winning products - Performance (affiliate), Creator (influencer), and Advocate (customer referral) - unify every type of partner into one integrated platform. As consumers increasingly rely on recommendations from people and communities they trust, impact.com helps brands show up where it matters most. Today, over 5,000 global brands - including Walmart, Uber, Shopify, Lenovo, L’Oréal, and Fanatics - rely on impact.com to power more than 350,000 partnerships that deliver measurable business results.

Your Role at impact.com:

We're seeking a Senior Data Scientist to serve as an embedded Data Scientist within our Programmatic Experience Group. You'll own the design and deployment of machine learning models that optimize yield, pricing, and inventory allocation at scale — sitting at the intersection of data science, platform engineering, and marketplace economics.

This is a high-craft, high-ownership individual contributor role. You'll work end-to-end: architecting the data pipelines that feed your models, engineering the features that drive performance, and deploying real-time inference systems that make decisions at speed. Your work directly determines how effectively Impact's programmatic marketplace balances advertiser performance with publisher monetization — making this one of the highest-leverage technical roles in the business.

You'll collaborate closely with Product, Data Science, and Programmatic Delivery Engine Engineering, but you operate with significant autonomy. You're expected to bring both the modeling rigor of a data scientist and the production instincts of an ML engineer — and to be genuinely excited about both.

What You'll Do:

Yield Optimization & Pricing Models

• Design and deploy ML models that optimize auction pricing, bid shading, floor price setting, and yield across Impact's programmatic inventory.
• Build and iterate on real-time pricing algorithms that balance short-term revenue efficiency with long-term publisher and advertiser health.
• Develop and maintain feedback loops that allow pricing models to adapt to shifting market conditions, inventory mix, and demand patterns.
• Quantify the revenue impact of pricing model improvements; communicate tradeoffs between yield maximization, fill rate, and partner ROI to stakeholders.

Inventory Allocation & Supply Optimization

• Own ML-driven inventory allocation logic: routing, pacing, and matching supply to demand across partner segments, deal types, and campaign objectives.
• Build models that forecast inventory availability, demand curves, and clearing prices to support proactive allocation decisions.
• Identify and address inefficiencies in inventory utilization — including unsold inventory, suboptimal deal matching, and allocation imbalances across the publisher base.

Data Architecture & Feature Engineering

• Design and own the data infrastructure that feeds programmatic models: event pipelines, feature stores, training datasets, and real-time feature serving.
• Engineer high-signal features from auction logs, bid stream data, user signals, contextual attributes, and historical performance — at the scale of programmatic data volumes.
• Build robust data pipelines with production-grade standards: reliability, observability, versioning, and efficient reprocessing.

Real-Time Inference & Production ML

• Deploy models to production real-time inference environments; own latency, reliability, and throughput requirements for auction-time decision-making.
• Build monitoring systems that track model performance, data drift, and system health in production; define alerting thresholds and retraining triggers.
• Partner with MLOps and Platform Engineering to ensure scalable, low-latency serving infrastructure meets SLOs under high-volume auction traffic.
• Own the full model lifecycle: training, evaluation, deployment, A/B testing, and iteration.

Experimentation & Performance Measurement

• Design and execute rigorous A/B and holdout experiments to measure the causal impact of model changes on yield, fill rate, advertiser performance, and publisher revenue.
• Build evaluation frameworks that go beyond offline metrics — validating model behavior in live auction environments where feedback signals are delayed or noisy.
• Translate experimental results into clear business narratives; present findings and recommendations to Product and business stakeholders.

Self-Learning Systems & Feedback Loops

• Research and implement adaptive, self-learning components within the programmatic stack — including contextual bandits, reinforcement learning signals, and online learning approaches where appropriate.
• Design feedback mechanisms that close the loop between auction outcomes, model updates, and system behavior; reduce reliance on manual tuning and rule-based overrides.
• Stay current with advances in programmatic ML, auction theory, and online optimization; evaluate applicability to Impact's specific marketplace dynamics.

Cross-Functional Collaboration

• Serve as the primary ML technical partner for the Rubicon product and engineering teams; translate business requirements into modeling approaches and communicate technical tradeoffs clearly.
• Collaborate with Data Science peers on shared infrastructure, modeling standards, and cross-domain feature reuse.
• Document models, architectures, and experimental findings to a standard that enables review, replication, and knowledge transfer across teams.

What You Bring:

Required

• Experience: 5+ years in data science, ML engineering, or quantitative research, with at least 2+ years building and deploying ML models in programmatic advertising, ad tech, marketplace optimization, or a closely related domain (e.g., real-time bidding, dynamic pricing, auction systems).
• Programmatic & marketplace depth: Demonstrated understanding of programmatic auction mechanics (RTB, header bidding, floor pricing, deal types, bid shading) and how ML can be applied to optimize outcomes across the supply-demand stack.
• Production ML engineering: Proven ability to take models from prototype to production independently — including real-time inference, monitoring, retraining pipelines, and SLO ownership.
• Data architecture: Experience designing and building data pipelines, feature stores, and training infrastructure for high-volume, low-latency ML systems.
• Technical skills:
• Strong Python and SQL; proficiency with ML libraries (scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow) and large-scale data tools (Spark, Kafka, or equivalent streaming/batch frameworks).
• Experience with real-time feature serving and low-latency model deployment (REST APIs, gRPC, or streaming inference).
• Familiarity with production ML workflows: model versioning, drift monitoring, A/B testing, evaluation, and retraining.
• Experience processing and modeling at programmatic data scale: high-cardinality auction logs, bid stream data, impression and click events.
• Experimentation rigor: Strong grasp of causal inference and experiment design in online, delayed-feedback environments (auction holdouts, switchback tests, variance reduction techniques).
• Communication: Ability to explain complex modeling decisions and tradeoffs to Product and business stakeholders; comfortable presenting in cross-functional forums.
• Education: Bachelor's in a quantitative field (CS, Statistics, Math, Engineering, Economics, or similar); Master's/PhD preferred.

Preferred / Nice to Have

• Direct experience with SSP, DSP, or exchange-side yield optimization — particularly floor price optimization, bid landscape modeling, or deal matching algorithms.
• Familiarity with auction theory (first-price vs. second-price dynamics, optimal reserve pricing, revenue equivalence) and its practical implications for programmatic ML.
• Experience with contextual bandits, multi-armed bandits, or reinforcement learning applied to real-time decisioning problems.
• Knowledge of online learning and adaptive algorithms in production environments with non-stationary data distributions.
• Familiarity with privacy-preserving ML techniques relevant to programmatic (differential privacy, federated learning, cookieless attribution modeling).
• Experience with GCP tools (BigQuery, Vertex AI, Dataflow, Pub/Sub) and/or Databricks/Spark for large-scale event processing and model training.
• Exposure to supply forecasting, inventory management, or capacity planning in programmatic or marketplace contexts.
• Familiarity with Impact's affiliate and partnership ecosystem, or prior experience at the intersection of performance marketing and programmatic delivery.

What Sets You Apart

• Marketplace intuition. You understand programmatic auctions not just as an engineer but as an economist — you think about incentive structures, equilibrium dynamics, and how model decisions ripple through the supply-demand stack.
• Full-stack ML ownership. You're as comfortable designing a feature store schema as you are tuning a gradient boosting model or debugging a latency spike in production. You own the whole chain.
• Feedback loop thinking. You don't just deploy models — you design the systems that make them smarter over time. You think about how today's decisions become tomorrow's training signal.
• Rigor under real-world constraints. You know how to run clean experiments in environments where feedback is delayed, data is noisy, and business pressures create tradeoffs. You don't let imperfect conditions become an excuse for imprecise thinking.
• Pragmatic delivery. You ship. You balance the perfect with the production-ready, iterate fast, and know when an MVP outperforms a six-month research project.
• Collaborative depth. You build genuine technical trust with engineering and product partners — not just by having good ideas, but by following through, communicating clearly, and making the integration easy.

Salary Range: $165,000 - $185,000 per year, plus an additional 5% variable annual bonus contingent on Company performance and eligible to receive a Restricted Stock Unit (RSU) grant.

*This is the pay range the Company believes is equitable for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time.

Benefits and Perks: 

At impact.com, we believe that when you’re happy and fulfilled, you do your best work. That’s why we’ve built a benefits package that supports your well-being, growth, and work-life balance.

• Medical, Dental, and Vision insurance
• Office-only catered lunch every Thursday, a healthy snack bar, and great coffee to keep you fueled 
• Flexible spending accounts and 401(k)
• Flexible Working: Our Responsible PTO policy means you can take the time off you need to rest and recharge. We're committed to a positive work-life balance and provide a flexible environment that allows you to be happy and fulfilled in both your career and your personal life.
• Health and Wellness: Your well-being is a priority. Our mental health and wellness benefit includes up to 12 fully covered therapy/coaching sessions per year, with additional dependent coverage. We also offer a monthly gym reimbursement policy to support your physical health.
• A Stake in Our Growth: We offer Restricted Stock Units (RSUs) as part of our total compensation, giving you a stake in the company's growth with a 3-year vesting schedule, pending Board approval.
• Investing in Your Growth: We’re committed to your continuous learning. Take advantage of our free Coursera subscription and our PXA courses.
• Parental Support: We offer a generous parental leave policy, 26 weeks of fully paid leave for the primary caregiver and 13 weeks fully paid leave for the secondary caregiver.
• Technology Financial Support: We provide a technology stipend to help you set up your home office and a monthly allowance to cover your internet expenses. 

impact.com is proud to be an equal-opportunity workplace. All employees and applicants for employment shall be given fair treatment and equal employment opportunity regardless of their race, ethnicity or ancestry, color or caste, religion or belief, age, sex (including gender identity, gender reassignment, sexual orientation, pregnancy/maternity), national origin, weight, neurodivergence, disability, marital and civil partnership status, caregiving status, veteran status, genetic information, political affiliation, or other prohibited non-merit factors.

#LI_Seattle

About the role

Join us to build the measurement and decision engine for patient growth.

As a Staff Data Scientist, Growth, you will be the senior analytical and strategic leader who makes marketing performance legible, credible, and actionable. You will partner closely with Growth Marketing leadership and channel owners across paid, lifecycle, and organic, plus Finance, Product, and Engineering. Your job is to help Headway answer the questions that matter:

• What is truly incremental?
• Where should we invest next?
• What is driving performance shifts?
• How do we scale what works without fooling ourselves?

You will build the frameworks, analyses, and modeling approaches that enable the marketing team to move faster with confidence. This is high-stakes decision support for a growth engine that needs to compound and certainly not a dashboard-only role or “just attribution” role. 

What you will do

• Own incrementality measurement across channels. Design and analyze geo tests, holdouts, lift tests, and quasi-experimental approaches when randomized tests are not feasible. Define clear guardrails, decision rules, and what “good” looks like.
• Build a marketing measurement system that leaders trust. Define canonical metrics (CAC, LTV, payback, conversion, retention, capacity-adjusted ROI), ensure definitions are consistent, and create a clear measurement narrative that aligns Marketing, Finance, and Product.
• Turn ambiguity into a plan. When performance changes, you will diagnose why, quantify contributing drivers, and recommend concrete actions. You will be the person who can say, “Here’s what moved, here’s why we believe it moved, and here’s what we do next.”
• Develop and evolve modeling approaches where they create leverage. Build practical models such as LTV and retention forecasting, cohort value prediction, causal uplift models for lifecycle, and marketing mix modeling when appropriate. Focus on models that survive contact with reality: calibration, backtesting, and decision usefulness.
• Partner with Engineering on the measurement plumbing. Improve event instrumentation, identity resolution assumptions, offline conversion integration, and data quality monitoring so measurement is robust. Advocate for minimal, decision-critical requirements that unlock reliable learning.
• Design learning loops that scale. Create repeatable experimentation and analysis templates for channel and creative testing, including measurement of message by audience by surface. Increase testing velocity without lowering the truth standard.
• Influence strategy, not just reporting. Bring an evidence-based point of view on channel allocation, growth constraints, saturation, diminishing returns, and the tradeoffs between short-term acquisition and long-term retention and care outcomes.
• Uplevel the team. Mentor analysts and data scientists working on growth, set quality standards, and help establish best practices across experimentation, causal inference, and forecasting.

What will make you successful

• 10+ years using data science, analytics, and experimentation to drive decisions in marketing, growth, or marketplace environments (or equivalent scope and demonstrated impact).
• Deep expertise in causal inference and incrementality in real-world marketing systems: you know the failure modes (selection bias, channel cannibalization, platform noise, attribution myths) and how to design around them.
• Strong SQL plus strong proficiency in Python or R, with the ability to build reliable, reusable analytical workflows.
• Practical modeling skill, especially as applied to marketing and growth: cohorting, forecasting, LTV estimation, saturation and diminishing returns, MMM concepts, calibration and monitoring.
• Track record of influencing executive decisions with clear recommendations and measurable outcomes, not just analysis.
• Excellent communication: you can make complex measurement logic understandable and defensible to non-technical partners, and you can call out uncertainty without losing momentum.
• High ownership and strong judgment: you prioritize what changes decisions, you move quickly, and you know when to slow down because the risk is real.
• You are motivated by the mission. Access and affordability in mental healthcare are not abstract problems here.

Nice to have

• Experience with geo experiments, marketplace constraints, or capacity-aware marketing optimization.
• Experience measuring acquisition quality beyond conversion: downstream engagement, retention, clinical matching quality, and unit economics.
• Familiarity with lifecycle marketing measurement (incrementality, uplift, experimentation design for messaging).
• Experience partnering with Finance on budget allocation, payback, and scenario planning.
• Comfort working with imperfect identity, privacy constraints, and evolving attribution ecosystems.

Compensation and Benefits:

The expected base pay range for this position is $212,000 - $265,000, based on a variety of factors including qualifications, experience, and geographic location. In addition to base salary, this role may be eligible for an equity grant, depending on the position and level.

We are committed to offering a comprehensive and competitive total rewards package, including robust health and wellness benefits, retirement savings, and meaningful ownership opportunities through equity. Compensation decisions are made holistically, ensuring fairness and alignment with market benchmarks while recognizing individual contributions and potential.

• Benefits offered include:
• Equity compensation
• Medical, Dental, and Vision coverage
• HSA / FSA
• 401K
• Work-from-Home Stipend
• Therapy Reimbursement
• 16-week parental leave for eligible employees
• Carrot Fertility annual reimbursement and membership
• 13 paid holidays each year as well as a Holiday Break during the week between December 25th and December 31st
• Flexible PTO
• Employee Assistance Program (EAP)
• Training and professional development

Your Impact

We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a key member of our research and development efforts, you will play a crucial role in advancing the state-of-the-art in Large Language Models (LLMs), Multimodal Large Language Models (MLLMs), Computer Vision and GenAI technologies for law enforcement and beyond. You will collaborate with cross-functional teams to design, develop, and deploy cutting-edge LLM, MLLM, CV models and algorithms and solutions that enable intelligent reasoning, perception and understanding of multimodal data.

What You’ll Do
Location: any cities with Axon Engineering Hub in US, Vietnam, EU (see https://www.axon.com/company)

• US: Seattle, Boston, Scottsdale

Responsibilities

• Own one or more key technical areas across LLM, MLLM, CV product portfolio.
• Provide technical leadership to junior scientists, guiding the transition of R&D concepts into impactful Axon product feature.
• Research and develop cutting-edge techniques in LLM, MLLMs, GenAI, and Computer Vision across cloud, devices and sensors based data sources.
• Design and implement efficient and scalable MLLM models for inference and analysis of multimodal data.
• Explore novel approaches to address challenges in NLP, NLU, Object Detection, Object Recognition, Object Tracking, Segmentation, and Scene Understanding.
• Optimize AI models, algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.
• Evaluate the performance of LLM, MLLM, CV models using real-world datasets and design experiments to validate their effectiveness.
• Stay up-to-date with the latest research trends and advancements in computer vision, machine learning, and deep learning, MLLMs, GenAI and integrate relevant findings into our projects.
• Contribute to patent disclosures, academic publications, and technical documentation to share insights and findings with the broader community.
• Experience coach and mentor junior scientists.

What You Bring

• PhD and with +5 years for ML Scientist, +8 years for Sr. ML Scientist, +10 years for Principal ML Scientist experience in Computer Science or a related field with a focus on LLM, MLLMs, Computer Vision, GenAI.
• Proven track record of research excellence in LLM, MLLM, Computer Vision, Robotics Perception, GenAI, demonstrated through publications in top-tier conferences or journals.
• Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system.
• Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
• Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges
• Experience in developing computer vision algorithms for resource-constrained devices such as mobile phones, IoT devices, or embedded systems is highly desirable.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesday through Friday, with flexibility to work remotely on Mondays. We believe connection fuels innovation, and our in-office culture is designed to support meaningful teamwork and mentorship.

About the Role

As a Technical Deployment Lead on the Claude Agentic Solutions team, you will lead the delivery of custom AI agent solutions for enterprise customers in highly regulated industries. You'll own high-value engagements where we collaborate directly with customers to build and deploy agents into their most critical business processes.

This is a founding team: you will help us to build technical playbooks and define the processes and repeatable patterns needed for us to scale this emerging motion. You will champion our mission in the field, ensure world class delivery, and bring insights back to our product and research teams on a regular basis.

You'll own engagements end-to-end, from SOW through production deployment. You'll work alongside Forward Deployed Engineers who build the technical solution, while you own product scoping, stakeholder management, value measurement, and the organizational complexity that comes with deploying AI agents in enterprise environments. You need to be technical enough to hold architecture conversations with engineering stakeholders and polished enough to run executive briefings with C-suite sponsors.

Responsibilities

• Own the technical delivery plan for each engagement. Structure SOWs with clear scope, milestones, dependencies, success criteria, and value hypotheses. Translate customer business objectives into a sequenced roadmap that FDEs execute against.
• Lead technical discovery. Map customer workflows, identify constraints, define MVP scope, and shape the solution architecture for custom agent deployments.
• Run day-to-day engineering execution. Drive delivery across Anthropic and customer teams. Keep progress unblocked and sequenced. Make real-time trade-offs on scope and priority to protect the critical path.
• Own product scoping for field engagements. Define the MVP, author requirements documentation, prioritize the engineering backlog, and manage scope against success criteria as requirements evolve.
• Own the customer relationship throughout delivery. Lead executive briefings, manage stakeholder communications across technical leads and procurement, and represent Anthropic's technical credibility with senior business and engineering leaders.
• Own value measurement and ROI. Define impact hypotheses, set baselines and KPIs, run pre- and post-deployment measurement, and report outcomes to executive sponsors.
• Codify reusable delivery assets. Build solution patterns, evaluation frameworks, and technical playbooks. Extract what works across engagements and feed field signals back to Product and Research to improve our platform and models.
• Navigate enterprise and regulatory complexity. Security reviews, legal approvals, procurement processes, compliance requirements, and organizational dynamics.
• Manage scope and change. Handle evolving requirements, set expectations, negotiate contract modifications, identify risks early, and escalate with clear context when needed.
• Run delivery operations. Sprint ceremonies, milestone reviews, and progress reporting.
• Travel to customer sites. Build relationships, unblock delivery, and accelerate adoption. (25–50% expected).

You May Be a Good Fit If You

• Have led AI/ML engagements/deployments, whether as a founder, data scientist, engineer, researcher, or in a professional services or consulting role.
• Have delivered AI, ML, or LLM-based agentic solutions into production. You understand solution patterns, integration approaches, and what breaks in real environments.
• Have experience in a specialized vertical (financial services, life sciences, pharmaceutical, retail, mining, agriculture, etc.).
• Can lead architecture discussions with engineering stakeholders, evaluate technical trade-offs, and pressure-test technical decisions. You won't write production code, but you will own the technical direction of engagements alongside FDEs.
• Have a track record delivering complex, high-stakes technical projects for enterprise clients where outcomes depended on tight coordination and fast decision-making — ideally across multiple workstreams in regulated industries.
• Have executive presence — polished, credible, and comfortable representing Anthropic to senior leaders in high-stakes environments.
• Thrive in ambiguity and bring structure where none exists.
• Have a builder's mindset — you're here to create a function, not join one.

Applied Research Scientist - Life Science Partnerships

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest, but we have employees who live across the country.  Our team enjoys the flexibility of a hybrid model and working from anywhere.  In person attendance is required at least once per year for an onsite meeting. 

For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time. #LI-remote

Who We Need 

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. 

This Opportunity 

This Applied Research Scientist, Strategic Partnerships position is a high impact, customer-facing role that requires a diverse set of skills spanning technical execution, applied research methodology, and relationship management. You will work directly with life sciences partners to translate research questions into analytical approaches, execute studies using real-world Electronic Health Record (EHR) data (~120M+ patients), and guide customers in best practices for real-world evidence generation.

You will play a key role in advancing customer research by helping shape analytical approaches, ensuring methodological rigor, and driving projects forward from question to insight. While customers may define or co-develop study protocols, you will provide guidance on study design, bias considerations, statistical approaches, and interpretation of results. This role requires balancing rapid-response analytical support with deeper, more complex investigations, while maintaining a high bar for scientific rigor and customer experience.

Responsibilities

• Partner closely with life sciences customers to understand research questions and translate them into analytical approaches
• Required to excel in providing technical analytics support as well as directly working with customers on calls to troubleshooting customer analysis.
• Use technical skills to scope out customer analyses requests, produce studies and results using SQL, R and Python within an agreed upon deadline.
• Build strong, trusted relationships with customer stakeholders, acting as a key partner in advancing their research goals
• Apply appropriate research methodologies, including cohort design, bias mitigation, and statistical analysis
• Communicate on the status of various projects and collaborate with success managers to ensure that Truveta clients can be successful with the platform.
• Guide customers on best practices in real-world data research, including study design tradeoffs and interpretation of results
• Lead customer-facing discussions to unblock research challenges and drive projects forward
• Collaborate with customers to support peer-reviewed publications and high-quality research outputs
• Deliver both rapid-response analyses and deeper, in-depth investigations depending on customer needs
• Provide technical support and troubleshooting for customer analyses, code, and notebooks
• Create enablement materials as the Truveta platform evolves to help onboard new researchers to our increasing capabilities.
• Collaborate cross-functionally to investigate data quality and demonstrate data reliability
• Deliver feedback to internal teams based on customer requests to inform Truveta’s product roadmap.

Required Skills

• Undergraduate or graduate degree in clinical research, epidemiology, biostatistics, data science, clinical informatics, or a related field
• 5+ years of experience working in a technical customer-facing role, delivering high-quality research studies & analyses.
• 3+ years of experience wrangling and analyzing Electronic Health Record data or other Real World Data sources in life science companies, CROs, other EHR data companies or healthcare organizations.
• Strong proficiency in SQL, R and/or Python for statistical analysis
• Experience working across large, multi-domain healthcare datasets with millions of patients and hundreds of millions of records, leveraging distributed computing frameworks for scalable analysis.
• Willingness to learn new coding languages including internal proprietary coding language to analyze data and build cohorts.
• Strong understanding of real-world evidence principles, including bias, confounding, and study design considerations.
• Demonstrated experience applying research methodologies, including cohort design and statistical approaches.
• Experience delivering high-quality product demonstrations that enable customers or stakeholders to understand and effectively leverage data, platform capabilities, and analytical workflows.
• Proven ability to learn, adapt, and independently drive multiple projects forward in a fast-paced, start-up environment.
• Strong executive presence with the ability to build credibility and trust across stakeholders and effectively communicate complex technical concepts to both executive and technical audiences.

Preferred Qualifications

These qualifications are preferred but not required. Candidates will have opportunities to develop these skills over time.

• Advanced degree (MS, MPH, PhD) in epidemiology, biostatistics, health economics, or related field
• Experience supporting or contributing to peer-reviewed publications or conference abstracts
• Knowledge of advanced statistical methods such as regression, propensity score methods, survival analysis, and longitudinal data analysis
• Experience applying methods for causal inference or handling incomplete data in observational research
• Experience with Spark/PySpark or distributed data processing
• Experience with Regression, Propensity Score Matching, Kaplan-Meier Analyses, or Survival Analyses
• Experience working in customer-facing or consulting-style roles
• Demonstrated ability to present research findings to both technical and non-technical audiences

Why Truveta?   

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together.  

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $130,000 to $160,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

ML Postdoc Researcher - LLMs & Generative AI

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Our headquarters are in the greater Seattle area, but we celebrate and embrace a remote culture.  Participation in the Postdoctoral Research program requires that you are physically present in the United States for the duration of the program. #LI-remote

Who We Need 

We are seeking a highly motivated and talented Machine Learning Postdoctoral Researcher to join our AI research team and contribute to our innovative projects in the field of Large Language Modeling (LLM) and clinical data analysis. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you.

Program Details

Our Postdoctoral Research program is designed for candidates who have completed their PhD within the last two years and worked in their area of expertise since graduation as a postdoc, professor, or industry researcher/scientist. Candidates are expected to demonstrate both independence in defining their research strategy within a domain as well as an ability to apply innovative solutions to our products. Our postdoc research programs are designed to be a minimum of 3 months and a maximum of 12 months, with the opportunity to extend beyond the initially agreed term based on the company’s needs and the candidate’s desires.

This Opportunity

We are looking for machine learning experts who can utilize applied science and software development skills in building our Foundation Models that help us address some of the hardest problems towards our vision of Saving Lives with Data. You will work in an exciting and fast-paced environment, collaborating closely with multiple teams across the company. You will work as part of an organization that brings together talent from diverse backgrounds including software engineering, big data, machine learning and AI, clinical informatics, and medicine making our team an exciting place to work. We value and encourage diversity in the belief that our differences make us and our products better.

In this role, you will:

• Collaborate with researchers and engineers to design, develop, and refine large language models and generative models for various applications.
• Utilize your expertise in machine learning and natural language processing to develop novel algorithms and methodologies for generative modeling tasks.
• Implement, train, and fine-tune LLM and GPT-like models on large-scale datasets to ensure optimal performance and accuracy.
• Stay up to date with the latest research advancements and techniques in the field of language modeling, generative modeling, and machine learning.
• Deliver the next generation of innovation in trustworthy healthcare.

Key Qualifications

• Ph.D. in Computer Science, Electrical Engineering, or a related field, with a focus on machine learning, natural language processing (NLP), Large Language Models (LLMs), multi-modal foundation models, and generative AI
• Strong theoretical and practical background in NLP including experience with state-of-the-art architectures
• Proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow, etc.) and libraries commonly used in NLP and Generative AI
• Solid programming skills in Python and the ability to write clean, efficient, and well-documented code
• Excellent problem-solving and troubleshooting abilities, along with a strong analytical mindset and persistence in resolving problems
• Strong communication skills and the ability to work effectively in a collaborative research environment

Preferred Qualifications

• Experience with distributed parallel training, large-scale multi-modal foundation and generative models
• Familiarity with parameter-efficient tuning techniques, Reinforcement Learning from Human Feedback (RLHF), and prompt engineering techniques
• Familiarity with training multi-modal foundation models
• Familiarity with cloud-based infrastructure and experience deploying large-scale machine learning models in production environments
• A track record of publications and contributions to the machine learning and natural language processing communities

This postdoctoral research program offers a unique chance to work on state-of-the-art language models and contribute to transformative research with the vision of Saving Lives with Data. You will be part of a dynamic team of researchers and engineers who are passionate about pushing the boundaries of machine learning and natural language understanding in the healthcare domain. Join us and make a significant impact on the future of healthcare and patient well-being.

Why Truveta? 

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together. 

We offer: 

• Competitive compensation
• Company-issued laptop and equipment
• Opportunities for future full-time positions
• The range for this position is $50-$60 per hour

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Senior Applied Research Scientist – Oncology

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest, but we have employees who live across the country. Our team enjoys the flexibility of a hybrid model and working from anywhere.  In person attendance is required for two weeks during the year for Truveta Planning Week.

For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time. #LI-remote

Who We Need

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. 

This Opportunity 

Truveta is seeking a motivated, innovative, and technical Applied Research Scientist with expertise in oncology to join Truveta Research. Truveta Research is an internal research organization focused on demonstrating what’s possible with Truveta by producing high-interest, high-quality, trusted research. As an Applied Research Scientist, you will collaborate closely with a broad set of collaborators across communications, marketing, engineering, product, and fellow scientists to push the boundaries of what can be achieved with healthcare data, transforming complex datasets into impactful research. You will have the opportunity to work with an extensive, high-quality dataset of real-world Electronic Health Records (EHR), encompassing over 100 million patients, including rich longitudinal oncology data such as diagnosis, staging, biomarkers, treatments, and outcomes. Your work will generate insights that advance cancer care, improve patient outcomes, and meaningfully contribute to public health—while upholding the highest standards of clinical and scientific rigor.

Responsibilities

• Proactively initiate and drive applied research studies focused on oncology, from ideation through peer-review publication.
• Apply appropriate and rigorous methods for observational data studies, such as causal inference methods, missing data approaches, survival analysis, longitudinal data analysis, and time series analysis.
• Write, review, and maintain code (R or Python) to process, wrangle, and analyze data, identifying problems, devising solutions, and creating methodologies that drive data insights and best practices.
• Be accountable to agreed upon timelines for delivering research studies, working to communicate and manage dependencies.
• Proactively manage several projects simultaneously to maximize impact and efficiency of your work.
• Work collaboratively with internal and external stakeholders, including engineering, product, clinical informatics, and communications.
• Represent researcher input by providing feedback on the development of research solutions that enable clinicians and researchers to address real-world healthcare challenges.

Required Skills

• Education: MD or PhD in Epidemiology, HEOR, Biostatistics, or a related field.
• Expertise in Applied Methods: Extensive experience with statistical and econometric methods for analyzing complex real-world data, including approaches for causal inference, handling incomplete data, modeling longitudinal or time-to-event outcomes, and working with structured or hierarchical data.
• Statistical Programming: 5+ years of hands-on experience with statistical programming in R and/or Python, with experience executing analysis plans intended for publication, particularly within the health sciences.
• Scientific publication: 5+ years of experience developing research publications, including peer-reviewed manuscripts and conference abstracts, including handling peer review.
• Cross-functional Collaboration: 3+ years of experience partnering with cross-functional teams and effectively communicating research findings and needs to non-technical stakeholders.
• Team-Oriented and Results-Driven: Proven ability to work within cross-functional teams to deliver research under tight deadlines.
• Presentation & Communication: Demonstrated ability to present complex research findings to both scientific and non-scientific audiences, adapting messaging and depth to the needs of clinicians, researchers, executives, media, and lay stakeholders.

Preferred Qualifications

• Thought leadership: Experience writing and/or speaking on real-world evidence, epidemiology, biostatistics, or related areas.
• Communication for lay audiences: Experience translating research findings for lay audiences.
• Scientific communication: Experience presenting research to both scientific and non-scientific audiences, tailoring complexity and interpretation for diverse stakeholders.
• Familiarity with EHR data models or clinical terminology: Understanding of oncology-relevant EHR data models, staging systems, tumor markers, treatment classes, and clinical vocabularies (e.g., ICD-10, SNOMED, LOINC, RxNorm).
• Ability to learn quickly: Demonstrated capacity to rapidly absorb new methods, tools, and domain knowledge in a fast-paced environment.

Why Truveta?   

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together.  

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $158,000 to $175,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

Senior Clinical Data Scientist - Applied Intelligence Solutions

Truveta is the world’s first health provider led data platform with a vision of Saving Lives with Data. Our mission is to enable researchers to find cures faster, empower every clinician to be an expert, and help families make the most informed decisions about their care. Achieving Truveta’ s ambitious vision requires an incredible team of talented and inspired people with a special combination of health, software and big data experience who share our company values.

Truveta was born in the Pacific Northwest, but we have employees who live across the country.  Our team enjoys the flexibility of a hybrid model and working from anywhere.  In person attendance is required at least once per year for an onsite meeting. 

For overall team productivity, we optimize meeting hours in the pacific time zone. We avoid scheduling recurring meetings that start after 3pm PT, however, ad hoc meetings occur between 8am-6pm Pacific time. #LI-remote

Who We Need 

Truveta is rapidly building a talented and diverse team to tackle complex health and technical challenges. Beyond core capabilities, we are seeking problem solvers, passionate and collaborative teammates, and those willing to roll up their sleeves while making a difference. If you are interested in the opportunity to pursue purposeful work, join a mission-driven team, and build a rewarding career while having fun, Truveta may be the perfect fit for you. 

This Opportunity 

We are seeking a Senior Clinical Data Scientist to join the Catalysts team, focused on applied intelligence solutions for Truveta.

This role focuses on building the concrete intelligence assets that intelligence uses to solve defined healthcare problems correctly and safely. You will work on concrete problem types such as safety monitoring, cohort feasibility, HEOR analyses, clinical trial workflows, and operational oversight, and be responsible for directly creating the knowledge assets, examples, and guardrails that intelligence uses to support these problems effectively and safely. 

A core part of the role is creating and maintaining practical intelligence assets that intelligence directly uses to support specific, repeatable solutions. These assets are contributed into a shared knowledge base maintained by the broader Catalysts team. 

You will also influence how intelligence consumes and applies knowledge by producing clear, reusable assets that translate complex technical and domain concepts into forms usable by both intelligence systems and non technical stakeholders. 

Out of scope: This role is not focused on model training, infrastructure, or large scale implementation. You are expected to be technically fluent and able to prototype, while deeper execution is handled collaboratively with peers who specialize in speed and scale. 

Responsibilities

• Intelligence solution construction: Independently build small scale, concrete intelligence solutions for specific healthcare problems by creating the required knowledge assets, examples, reference analyses, and guardrails that allow intelligence to answer the right questions and respect clear boundaries, within current platform capabilities.
• Domain problem breakdown: Break down healthcare problems in areas such as clinical research, HEOR, and clinical trials into the concrete assumptions, decision points, and data considerations that intelligence needs to handle correctly.
• Knowledge and guidance definition: Create and maintain the domain knowledge, guidelines, templates, and decision logic that intelligence systems need in order to perform effectively in each problem domain.
• Agent and workflow shaping: Shape how intelligence agents operate at a practical level by defining task breakdowns, decision logic, and required knowledge, working within current platform constraints.
• Knowledge extraction and transformation: Work with domain experts and users to extract assumptions, heuristics, and expertise, and convert them into structured inputs that intelligence systems can reliably consume.
• Generative AI reasoning: Apply an understanding of how generative AI systems retrieve and reason over knowledge to improve correctness, safety, and consistency of intelligence outputs, using concrete examples and test questions.
• Validation and guardrails: Define and validate constraints, exclusions, and limitations to ensure intelligence outputs are appropriate, trustworthy, and aligned with real world healthcare use.
• Collaboration and facilitation: Work closely with colleagues across the Catalysts team, contributing domain expertise, intelligence design, and reusable assets into a shared knowledge base, and collaborating as peers on intelligence solutions rather than owning a separate execution pipeline. 

Required Skills

• Education: Bachelor’s degree or equivalent experience in a quantitative or technical field such as computer science, data science, statistics, engineering, or a related discipline.
• Applied intelligence and LLM expertise: Strong understanding of how large language models consume, retrieve, and reason over knowledge, and how to structure information so it can be used efficiently and reliably by intelligence systems.
• Healthcare domain knowledge: Solid understanding of healthcare problem spaces such as clinical research, HEOR, clinical trials, and healthcare operations, and the types of questions and decisions users need support with.
• Generative AI fluency: Hands on experience using generative AI tools to synthesize, generate, and refine knowledge assets including guidance, templates, prompts, and structured explanations.
• Applied solution design: Ability to design and prototype applied intelligence solutions for specific problem types by combining domain knowledge, templates, prompts, guardrails, and workflows.
• Technical fluency: Comfortable writing and reviewing production quality analysis code (e.g., SQL, Python, or R) to prototype analyses, validate logic, and create reusable examples that intelligence and teammates can reuse. Deep engineering expertise is not required, but hands on technical fluency is expected.
• Knowledge creation and translation: Create clear, reusable intelligence assets by synthesizing expert input or authoring directly, translate technical and domain specific concepts into guidance that is understandable and actionable for a wide range of audiences, and explicitly define exclusions and limitations where intelligence should not provide answers. 

Preferred Qualifications

• Healthcare and EHR exposure: Experience working with healthcare or EHR data, including awareness of common data quality issues, biases, and clinical context.
• Decision support systems: Experience designing, evaluating, or contributing to decision support systems, recommendations, or intelligent assistants.
• Applied research background: Background in product analytics, applied research, or applied machine learning in support of real world decision making.
• Advanced technical depth: Experience building more complex analytical workflows, reusable code libraries, or data products that others rely on, even if this is not the primary focus of the role.
• Knowledge formalization: Experience translating expert knowledge into structured guidance, documentation, schemas, or training materials.
• Teaching and enablement: Teaching, mentoring, or enablement experience with analysts, researchers, or cross functional teams. 

Why Truveta?   

Be a part of building something special. Now is the perfect time to join Truveta. We have strong, established leadership with decades of success. We are well-funded. We are building a culture that prioritizes people and their passions across personal, professional and everything in between. Join us as we build an amazing company together.  

We Offer:

• Interesting and meaningful work for every career stage
• Great benefits package
• Comprehensive benefits with strong medical, dental and vision insurance plans
• 401K plan
• Professional development & training opportunities for continuous learning
• Work/life autonomy via flexible work hours and flexible paid time off
• Generous parental leave
• Regular team activities (virtual and in-person)
• The base pay for this position is $155,000 to $170,000. The pay range reflects the minimum and maximum target. Pay is based on several factors including location and may vary depending on job-related knowledge, skills, and experience. Certain roles are eligible for additional compensation such as incentive pay and stock options.

If you are based in California, we encourage you to read this important information for California residents linked here.

Truveta is committed to creating a diverse, inclusive, and empowering workplace. We believe that having employees, interns, and contractors with diverse backgrounds enables Truveta to better meet our mission and serve patients and health communities around the world. We recognize that opportunities in technology historically excluded and continue to disproportionately exclude Black and Indigenous people, people of color, people from working class backgrounds, people with disabilities, and LGBTQIA+ people. We strongly encourage individuals with these identities to apply even if you don’t meet all of the requirements.

Please note that all applicants must be authorized to work in the United States for any employer as we are unable to sponsor work visas or permits (e.g. F-1 OPT, H1-B) at this time. We appreciate your interest in the position and encourage you to explore future opportunities with us.

Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.

Our base salary range is $167,030 - $260,570, and in addition we have generous bonus plans to provide a competitive compensation package. 

Who You Are:

You are a creative, hands-on AI researcher with a strong foundation in AI and reasoning. Passionate about pushing the boundaries of research and engineering, you seek to advance AI both scientifically and openly. You thrive in collaborative environments, take initiative, and are eager to contribute to Ai2’s impact-driven mission in a dynamic, fast-paced research setting. Skilled at translating complex concepts into concrete research goals and implementation steps, you define clear approaches, execute effectively, and communicate results with clarity. You leverage these skills to create real-world benefits for researchers and practitioners alike and are excited to help drive the development of the best-performing open AI model.

Who We Are: 

We are a non-profit AI institute, focused on developing foundational AI research and innovation to deliver real-world impact through large-scale open models, the science of agentic systems, data, and artifacts (e.g., OpenScholar, OLMo, Tulu, and Scholar QA).   We unite the best and brightest scientific and engineering minds to explore the potential of truly open AI. Through our efforts we endeavor to empower academics, researchers, and AI developers more broadly to advance language models and reasoning-based agentic systems. Through close collaboration, we rapidly identify, define, and act on the most exciting and promising new ideas in AI.  

Our team is focused on developing agentic systems to revolutionize the way science is performed. We engage in language model post-training, generating and curating data, layering control strategies (e.g., POMDPs) atop LLMs, and developing novel methodologies to push the field forward. We study and evaluate AI models both theoretically and empirically, aiming to advance their capabilities. Additionally, we create impactful real-world applications, such as in scientific synthesis. Our goal is to develop state-of-the-art models that excel in scientific reasoning spanning literature synthesis, hypothesis formation, scientific coding, execution of computational experiments, and data analysis. These systems will collaborate with human scientists, not replace them.

Your Next Challenge:

As a key member of the core team of research scientists and machine learning engineers at Ai2, you will drive the development of AI systems with deep reasoning capabilities with a focus on the huge breadth of skills necessary for scientific reasoning. In this role, you will lead foundational research to advance agentic systems, shape our strategic direction, and lay the groundwork for future innovations. You will also work towards long-term ambitious research goals, while identifying intermediate milestones. 

The essential functions include, but are not limited to the following:

• Contribute to Ai2’s open source research environment to innovate,  study and advance the science of generative AI and agentic systems.
• Take a leading role in building artifacts and implementing software systems with real-world impact
• Author and present high-quality scientific technical reports, papers, and presentations
• Collaborate with and learn from team members across Ai2, including scientists and engineers
• Mentor early-career researchers and interns on their projects
• Develop collaborative relationships with relevant academic, industrial, government, and standards organizations

What You’ll Need:

• A PhD focusing on machine learning, reasoning, natural language processing, or a related area, with expertise in one or more of the following: reinforcement learning, experimental methodology, language models, the science of deep learning, or efficient algorithms for deep learning.  Curiosity about all of the above is a plus.
• The ability to own and pursue a research agenda to improve AI model reasoning capabilities.
• Enthusiasm for collaboration and teamwork on ambitious projects aligned with company goals.
• Experience leading a team to solve analytical problems (a plus).
• Contributions to open-source research libraries and an interest in continuing such work (a plus).

Physical Demands and Work Environment:

The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.

• Must be able to remain in a stationary position for long periods of time. 
• The ability to communicate information and ideas so others will understand. Must be able to exchange accurate information in these situations. 
• The ability to observe details at close range.
• Can work under deadlines.

A Little More About Ai2:

Ai2 is a Seattle based non-profit AI research institute founded in 2014 by the late Paul Allen. Our mission is building breakthrough AI to solve the world’s biggest problems. We develop foundational AI research and innovation to deliver real-world impact through large-scale open models, data, robotics, conservation, and beyond.

In addition to Ai2’s core mission, we also aim to contribute to humanity through our treatment of each member of the Ai2 Team. Some highlights are:

• We are a learning organization – because everything Ai2 does is ground-breaking, we are learning every day. Similarly, through weekly Ai2 Academy lectures, a wide variety of world-class AI experts as guest speakers, and our commitment to your personal on-going education, Ai2 is a place where you will have opportunities to continue learning alongside your coworkers. 
• We value diversity - We seek to hire, support, and promote people from all genders, ethnicities, and all levels of experience regardless of age. We particularly encourage applications from women, non-binary individuals, people of color, members of the LGBTQA+ community, and people with disabilities of any kind. 
• We value inclusion - We understand the value that people's individual experiences and perspectives can bring to an organization, and we are building a culture in which all voices are heard, respected and considered.
• We emphasize a healthy work/life balance – we believe our team members are happiest and most productive when their work/life balance is optimized. While we value powerful research results which drive our mission forward, we also value dinner with family, weekend time, and vacation time. We offer generous paid vacation and sick leave as well as family leave.
• We are collaborative and transparent – we consider ourselves a team, all moving with a common purpose. We are quick to cheer our successes, and even quicker to share and jointly problem solve our failures.
• We are in Seattle – and our office is on the water! We have mountains, we have lakes, we have four seasons, we bike to work, we have a vibrant theater scene, and we have so much else. We even have kayaks for you to paddle right outside our front door. We welcome interest from applicants from outside of the United States.
• We are friendly– chances are you will like every one of the 200+ (and growing) people who work here. We do. 

Ai2 is proud to be an Equal Opportunity employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. You may view the related Know Your Rights compliance poster and the Pay Transparency Nondiscrimination Provision by clicking on their corresponding links. 

This employer participates in E-Verify and will provide the federal government with your Form I-9 information to confirm that you are authorized to work in the U.S. If E-Verify cannot confirm that you are authorized to work, this employer is required to give you written instructions and an opportunity to contact the Department of Homeland Security (DHS) or Social Security Administration (SSA) so you can begin to resolve the issue before the employer can take any action against you, including terminating your employment. Employers can only use E-Verify once you have accepted a job offer and completed the Form I-9.

We are committed to providing reasonable accommodations to employees and applicants with disabilities to the full extent required by the Americans with Disabilities Act (ADA). If you feel you need a reasonable accommodation pursuant to the ADA, you are encouraged to contact us at recruiting@allenai.org.

Benefits:

• Team members and their families are covered by medical, dental, vision, basic life insurance, basic accidental death and dismemberment insurance, short-term disability, long-term disability, and an employee assistance program. 
• Team members are able to enroll in our voluntary life insurance program, our voluntary accidental death and dismemberment program, our health savings account plan, our healthcare reimbursement arrangement plan, and our health care and dependent care flexible spending account plans. 
• Team members are able to enroll in our company’s 401k plan. 
• Team members will receive $125 per month to assist with commuting or internet expenses and will also receive $200 per month for fitness and wellbeing expenses.
• Team members will also receive up to ten sick days per year, up to seven personal days per year, up to 20 vacation days per year and twelve paid holidays throughout the calendar year.
• Team members will be able to receive annual bonuses and can participate in the long-term incentive plan.

Note: This job description in no way states or implies that these are the only duties to be performed by the team members(s) of this position. Team members will be required to follow any other job-related instructions and to perform any other job-related duties requested by any person authorized to give instructions or assignments. All duties and responsibilities are essential functions and requirements and are subject to possible modification to reasonably accommodate individuals with disabilities. To perform this job successfully, the team member(s) will possess the skills, aptitudes, and abilities to perform each duty proficiently. Some requirements may exclude individuals who pose a direct threat or significant risk to the health or safety of themselves or others. The requirements listed in this document are the minimum levels of knowledge, skills, or abilities. This document does not create an employment contract, implied or otherwise, other than an at will relationship.

POSITION SUMMARY

Umoja Biopharma is seeking a driven Scientist to understand and assess the potency of lentiviral drug products. This role will develop early- and late-stage potency methods for release of drug substance/product and generate data packages to support regulatory submissions. The position will work closely with other functions to deliver qualified/validated QC release and characterization assays, generate associated documentation, and oversee transfer of methods internally or externally to a CMO/CRO.

As a laboratory-based position within the technical operations organization, this position will play a critical role in advancing Umoja’s pipeline and analytical development capabilities.

This role will be onsite 5 days/week based out of our Seattle, WA location.

CORE ACCOUNTABILITIES

Specific responsibilities include:  

• Successful design, execution, analysis, and documentation of experiments to develop analytical methods and key data packages for lentiviral gene therapies.

• Perform experiments to support analytical development and product characterization using advanced techniques including multicolor flow cytometry, ELISAs, Western blots, qPCR/dPCR, signal transduction and cytokine assays.

• Oversee the qualification of analytical methods.
• Author, review and approve technical documents including electronic notebook entries, standard operating procedures, test methods, technical reports, etc.

• Present findings on method development and communicate interpretation and strategic plans related to the potency of our drug product to cross-functional teams.
• Foster good teamwork and communication. Build a reputation of excellence as an individual and as a team.
• Collaborate with stakeholders within Analytical Development (Product Sciences and Process Analytics teams) and cross-functionally with Quality Control, CMC, Translational Medicine, Process Sciences, Discovery, and Vector Biology
• All other duties as assigned

The successful candidate will have:

• PhD/MS/BS in Immunology, Cellular Biology, Molecular Biology or related discipline with at least 0+/8+/10+ years of experience, respectively; equivalent combination of education and experience will be considered
• Proven track record in cell-based method development, including troubleshooting assays, experimental design, execution, and evaluation of data
• Ability to work in a fast-paced environment with broad responsibilities, meet deadlines, and prioritize work on multiple projects
• Strong communication skills in technical writing and oral presentation. Respectful of others and open to new ideas.

Preferred Qualifications:  

• Hands-on experience with multicolor flow cytometry, cell-based assays, ELISAs, viral transduction, and qPCR/dPCR
• Experience qualifying and transferring analytical methods to a QC lab or CMO/CRO
• Experience developing and qualifying potency methods according to ICH/USP guidelines and authoring method documentation

Physical Requirements:  

• Ability to perform standard laboratory tasks with appropriate PPE

• Perform physical tasks required to support laboratory work, including standing, walking, bending, kneeling, sitting, working with your hands in a biosafety cabinet, and occasionally moving materials up to 50 pounds
• Ability to spend prolonged periods of time working on a computer
• Ability to work onsite 5 days/week

Salary Range: $122,000 - $150,800

Data Scientist, Pricing

Location: Hyrbrid 4 onsite, 1 remote Seattle WA. 

Opendoor is transforming one of the largest, most complex markets in the world — residential real estate — using data at massive scale. Every pricing signal we generate directly impacts how we value homes, how we manage risk, and how efficiently capital moves through our marketplace. The work is highly leveraged: the quality of our pricing decisions influences conversion, margins, customer trust, and the company’s financial performance.

We are looking for mid to senior level Data Scientists. In this role, you will be a core driver of how Opendoor prices real estate at scale. You’ll operate at the intersection of economics, machine learning, experimentation, and product strategy — tackling ambiguity, shaping the pricing roadmap, and building models/analyses that materially move the business. Your insights will influence how we evaluate millions of dollars of housing inventory — and directly shape outcomes for our customers, our balance sheet, and the health of our marketplace.

What You’ll Do

• Build and maintain pricing metrics, dashboards, and frameworks.
• Run experiments and causal analyses to measure impact and drive decisions.
• Develop predictive + statistical models that improve pricing accuracy.
• Partner closely with Product, Engineering, and Operations teams to influence roadmap and model deployment.
• Deliver insights and narratives that inform executive strategy.

Skills & Qualifications

• Deep statistical reasoning: hypothesis design, experimental design, causal inference, and ability to distinguish signal vs noise.
• Proven end-to-end ML ownership: data acquisition, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Strong SQL + Python proficiency; comfortable working with production data pipelines and modern ML tooling (e.g., Spark, Airflow, Ray, SageMaker, Vertex, etc.).
• Demonstrated ability to translate complex analytical findings into clear business recommendations and influence cross-functional decision-making.
• Experience working with ill-defined problems and driving clarity on problem definition, success metrics, and realistic tradeoffs.
• High data-quality bar: disciplined approach to validation, bias analysis, and making decisions rooted in evidence vs intuition.
• Effective communicator — able to tell the story behind the model to both highly technical and non-technical audiences.
• 8+ years of experience in data science, product analytics, or a similar quantitative role.

Base salary range for this role varies. Generally, the base salary range is $186,000 – $256,000 annually + RSUs + ESPP + additional employee benefits (medical/dental/vision, life insurance, unlimited PTO, 401K).

#LI-RO

#

#LI-KC1

ABOUT THIS OPPORTUNITY

We are looking for a Data Scientist who views machine learning as a product, not just a research project. You will be a foundational member of our AI team, responsible for designing, building, and deploying sophisticated models that solve complex business problems. You aren't just an expert in XGBoost or Transformers; you are an expert in building the pipelines that make these models reliable, scalable, and impactful.

WHAT YOU'LL DO
^{Essential Job Duties & Functions}

• End-to-End Model Development: Design and implement the full ML lifecycle—from exploratory data analysis (EDA) and feature engineering to model selection, tuning, and validation.
• GCP Architecture: Leverage the full Google Cloud AI suite (Vertex AI, BigQuery ML, Dataflow, and Pub/Sub) to build robust, cloud-native ML solutions.
• MLOps & Engineering: Implement CI/CD for machine learning (CT - Continuous Training) to ensure models remain performant in production environments.
• Strategic Leadership: Partner with stakeholders to translate ambiguous business challenges into technical roadmaps. Mentor junior scientists and advocate for best practices in code quality and experiment tracking.
• Look for opportunities to embed AI as a repeatable co-pilot in daily workflows by integrating experimentation into real work, and continuously refining its use with sound judgment and validation.

WHAT YOU’LL BRING

• 5+ years in a professional Data Science role with a track record of deploying models at scale.
• Proficiency in Vertex AI, BigQuery, Cloud Storage, and Looker. Experience with Kubeflow is a major plus.
• Expert-level Python (pandas, scikit-learn, PyTorch/TensorFlow), Spark, and advanced SQL.
• Deep understanding of statistics and ML theory (e.g., Gradient Descent, Bias-Variance tradeoff, Bayesian inference).
• Experience with ETL/ELT processes, specifically using dbt.
• A strong curiosity for exploring new technologies, including AI
• A shared passion for and ability to demonstrate onX’s Company Values.
• Permanent US work authorization is a condition of employment with onX.

Our Tech Stack

• Data Warehouse: BigQuery
• Orchestration: Airflow (Cloud Composer)
• Modeling: Vertex AI Pipelines, JupyterLab
• Deployment: Docker, GKE (Google Kubernetes Engine)

Pro Tip for the Candidate: We value "clean code" as much as "smart math." If you treat your notebooks like production scripts and your Git history is a work of art, you’ll fit right in.

What Sets You Apart

• The "Product" Mindset: You understand that a model with 99% accuracy is useless if it costs more to run than the value it creates.
• Infrastructure as Code: You are comfortable with Terraform or similar tools to manage your cloud resources.
• Communication: You can explain the "why" behind a complex neural network architecture to an executive without using jargon.

THE ONX EXPERIENCE

onX is a distributed company with more than 400 employees across the country. We come together regularly to work in person and stay connected through regional basecamps and a culture that balances individual ownership with deep collaboration.

While we move quickly, we’re not a scrappy start-up. We operate with clear goals, structure, and frameworks that guide how we prioritize and execute. Priorities matter. While they may shift, data shapes how we evolve as our business, products, and the world around us change.

Clear priorities and structure don’t limit ownership - they make it possible. You’ll have the autonomy to define your work and make meaningful decisions within clear strategic boundaries. You’ll partner closely with others to solve complex problems and build solutions that scale across teams and platforms. Along the way, you’ll be supported with feedback, tools, and opportunities to grow your craft as you take on new challenges.

WHERE YOU CAN WORK

onX has created a thriving distributed workforce designed to foster connection, collaboration, and shared experience across several US locations. We have two HQ locations in Bozeman and Missoula, MT and established virtual workforce Basecamps in Austin, TX; Denver, CO; Kalispell, MT; Minneapolis, MN; Portland, OR; Salt Lake City, UT; and Seattle, WA.

HOW YOU’LL BE COMPENSATED

onX is committed to compensating all employees fairly and equitably for their contributions. For this position, applicants can expect to make between $126,000 to $149,000 upon hire. The pay range will vary based on experience, skills, certifications, and education among other factors as required in the job description. In addition, full-time onX employees are eligible for a grant of common share options with a vesting schedule and a potential annual bonus of 10% based on company performance.

WHAT WE’RE OFFERING YOU

• Competitive salaries, annual bonuses, equity, and opportunities for growth
• Comprehensive health benefits, including a no-monthly-cost medical plan
• Paid parental leave of 13 weeks for birthing parents and 5 weeks for non-birthing parents
• 401k matching at 100% for the first 3% you save and 50% from 3-5%
• Company-wide outdoor adventures and amazing outdoor industry perks
• Annual “Get Out, Get Active” funds to fuel your active lifestyle
• Flexible time away package that includes PTO, STO, VTO, and paid holidays

PERFORMANCE ESSENTIALS

In this role, success is driven by cognitive abilities such as concentration and problem-solving, essential for our computer-centric tasks. onX will explore reasonable accommodations to ensure that individuals with diverse abilities can fully engage in and contribute to the essential physical and mental functions of the job. If you need assistance or accommodation, please contact us at PC@onxmaps.com. 

Application Deadline is [day of week], [month] [day] at [0:00 pm] MST

Position open until filled. 

#LI-Remote

The Senior Data Scientist is responsible for working with the product manager and stakeholders to define and scope opportunities, using data to build novel products supporting the Flexe business model. They will identify and harvest data to power machine learning and/or optimization models for Flexe within the logistics and distribution industry. This role impacts organizational level goals. This job reports to the Data Products engineering manager. Additionally, this role is responsible for working with software engineers, data engineers, and analytics to deliver solutions.

Job Responsibilities

[50%] Experiment, prototype, and implement solutions to Flexe’s complex problems

• Research and define problems. Design experiments to prove theoretical models. Prototype implementations of new learning algorithms and/or prediction techniques.
• Driven by deep curiosity, use exploration and discovery techniques to build knowledge and technology which will inform decisions and solve problems.
• Obtain, evaluate, and interpret large amounts of data from various internal and external sources. 
• Design, build, test and release scientifically sound models to provide clients with insights and recommendations to improve their supply chains.

[25%] Technical leadership

• Lead the design, implementation and delivery of large feature releases.  Can work in parallel with other Data Scientists, BIEs, and analysts to deliver a product or solution.
• Proactively simplifies data modeling and code and resolves team architecture deficiencies.
• Influences or drives architecture decisions.  Can devise and assemble multiple components into a larger solution.

[25%] Teamwork - driving team processes and cross-functional collaboration

• Develop or evolve team processes to improve quality and delivery.
• Communicating verbally and in writing to business customers with various levels of technical knowledge, and sharing insights and recommendations.
• Collaborating with analysts, engineers, product managers, and stakeholders to design and implement software solutions for science problems.

Qualifications

Required Qualifications

• Requires a minimum of 8 years of related experience with a Bachelor’s degree; or 6 years and a Master’s degree; or a PhD with 3 years experience; or equivalent experience.
• Proficient in using scripting code (Python, R, etc.) to scrutinize data and build statistical and/or machine learning models.
• 5+ years of hands-on experience in predictive modeling, analysis, and machine learning.
• 5+ years of relevant working experience in an analytical role involving data extraction, statistical modeling, and communication.
• 3+ years of experience with data querying languages (SQL)
• Proven ability to work independently and communicate status clearly.  Workload is self-directed and organized.
• Proficiency in model development, model validation and model implementation for large-scale applications.
• Ability to convey mathematical results to non-science stakeholders.
• Strength in clarifying and formalizing complex problems.
• Natural curiosity and desire to learn, a passion for solving real world problems.

Preferred Qualifications

• Successful candidates will have a background in a quantitative field such as Machine Learning, Data Science, Statistics, Applied Mathematics, or Economics or 5+ years relevant experience.
• Supply chain experience within transportation, logistics, or warehousing.

#AS-LI

Your Impact

We are seeking a skilled and innovative Senior AI Research Scientist to join a new team focusing on agentic video and multimodal reasoning systems. As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in machine learning and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual and multimodal data.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

What You’ll Do

Reports to: Director of AI Research
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

• Collaborate with other scientists, engineers and product managers to build proof-of-concepts to shape the Axon of tomorrow.
• Lead end-to-end research efforts in AI-assisted universal search of and reasoning over large multimodal data with an emphasis on video understanding.
• Advance related computer vision, machine learning and gen-AI techniques for cloud and devices from multimodal data sources, including scene understanding, action recognition and anomaly detection.
• Design and implement responsible, privacy-preserving, efficient and scalable models for inference and analysis of visual data.
• Develop performance and quality metrics for agentic multimodal reasoning models and systems, and validate their effectiveness in real-world settings.
• Stay up-to-date with the latest research and advances in agentic AI, machine learning and computer vision and translate relevant findings into shipping Axon products.
• Contribute to academic publications, technical documentation, and patent disclosures to share insights and findings with the broader community.
• Coach and mentor junior scientists.

What You Bring

• PhD and 3+ years of experience in Computer Science or a related field with a focus on multimodal machine learning, large language models, video understanding, information retrieval, agentic reasoning or related technical fields.
• Proven track record of applied research and/or production impact in multimodal learning, video-language modeling, retrieval systems, foundation models, agentic systems, or RAG architectures.
• Experience owning and driving the ML development lifecycle from problem definition and data strategy through model development, evaluation, deployment, and iteration in production environments.
• Experience contributing to large-scale ML and multimodal RAG systems including embeddings, indexing and vector search at scale, distributed training or inference workflows, evaluation and ranking optimization, agentic tool use, and grounding LLMs with external knowledge.
• Strong understanding of video analysis and temporal modeling as well as computer vision fundamentals and trade-offs.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow or Keras.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

The Pay: Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 159,750 in the lowest geographic market and USD 234,300 in the highest geographic market. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit www.axon.com/careers/benefits.

#LI-Hybrid

Anthropic is at the forefront of AI research, dedicated to developing safe, ethical, and powerful artificial intelligence. Our mission is to ensure that transformative AI systems are aligned with human interests. We are seeking a Research Engineer to join our Pre-training team, responsible for developing the next generation of large language models. In this role, you will work at the intersection of cutting-edge research and practical engineering, contributing to the development of safe, steerable, and trustworthy AI systems.

Key Responsibilities:

• Conduct research and implement solutions in areas such as model architecture, algorithms, data processing, and optimizer development
• Independently lead small research projects while collaborating with team members on larger initiatives
• Design, run, and analyze scientific experiments to advance our understanding of large language models
• Optimize and scale our training infrastructure to improve efficiency and reliability
• Develop and improve dev tooling to enhance team productivity
• Contribute to the entire stack, from low-level optimizations to high-level model design

Qualifications:

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field
• Strong software engineering skills with a proven track record of building complex systems
• Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
• Familiarity with large-scale machine learning, particularly in the context of language models
• Ability to balance research goals with practical engineering constraints
• Strong problem-solving skills and a results-oriented mindset
• Excellent communication skills and ability to work in a collaborative environment
• Care about the societal impacts of your work

Preferred Experience:

• Work on high-performance, large-scale ML systems
• Familiarity with GPUs, Kubernetes, and OS internals
• Experience with language modeling using transformer architectures
• Knowledge of reinforcement learning techniques
• Background in large-scale ETL processes

You'll thrive in this role if you:

• Have significant software engineering experience
• Are results-oriented with a bias towards flexibility and impact
• Willingly take on tasks outside your job description to support the team
• Enjoy pair programming and collaborative work
• Are eager to learn more about machine learning research
• Are enthusiastic to work at an organization that functions as a single, cohesive team pursuing large-scale AI research projects
• Are working to align state of the art models with human values and preferences, understand and interpret deep neural networks, or develop new models to support these areas of research
• View research and engineering as two sides of the same coin, and seek to understand all aspects of our research program as well as possible, to maximize the impact of your insights
• Have ambitious goals for AI safety and general progress in the next few years, and you’re working to create the best outcomes over the long-term.

Sample Projects:

• Optimizing the throughput of novel attention mechanisms
• Comparing compute efficiency of different Transformer variants
• Preparing large-scale datasets for efficient model consumption
• Scaling distributed training jobs to thousands of GPUs
• Designing fault tolerance strategies for our training infrastructure
• Creating interactive visualizations of model internals, such as attention patterns

At Anthropic, we are committed to fostering a diverse and inclusive workplace. We strongly encourage applications from candidates of all backgrounds, including those from underrepresented groups in tech.

If you're excited about pushing the boundaries of AI while prioritizing safety and ethics, we want to hear from you!

This position is on-site in Seattle, WA.

Join Lumen Bioscience as a Scientist II, Process Development to lead the development, optimization, and qualification of scale-down models for upstream and downstream processes supporting complex biologics in an innovative early-stage manufacturing environment. In this role, you will apply process modeling DoE strategies to maximize product potency and productivity, design and execute complex experimental studies using sound statistical methodologies, and lead technology transfer efforts across Lumen's portfolio.

This position is a strong fit for someone who brings deep scientific expertise, thrives on independently driving complex technical initiatives, and excels in a highly cross-functional environment. You will collaborate closely with Manufacturing and R&D teams to ensure alignment and successful program execution, clearly communicate scientific strategy, risks, data interpretations, and recommendations to project teams, leadership, and internal and external partners. You will also author technical reports, protocols, and presentations, execute assigned milestones on time while upholding high scientific standards. You will also have the opportunity to supervise and mentor junior team members.

Lumen’s breakthrough biologics manufacturing and administration platform addresses critical challenges from patient accessibility to global climate change. The Process Development Scientist II will lead development, optimization, and qualification of scale-down models (SDM) for upstream and downstream processes supporting complex biologics. This role is central to advancing robust process understanding, enabling efficient technology transfer, and will have the opportunity to contribute to Lumen’s innovative platform manufacturing process.

If you are a resourceful, detail-oriented scientist with sound judgement, strong organizational skills, and the ability to manage multiple priorities while delivering high-quality results in a fast-paced and evolving environment, we encourage you to apply.

Duties & Responsibilities:

This position requires working under the 21 CFR part 210/211 standard pharmaceutical cGXP quality system processes.

• Lead the development, optimization, troubleshooting, and qualification of scale-down models for upstream and downstream processes for complex biologics
• Design, execute, and analyze complex experimental studies using sound statistical and DoE methodologies
• Lead technology transfer efforts
• Timely execution of assigned milestones while maintaining high scientific standards
• Collaborate cross-functionally with Manufacturing and Research and Development teams to ensure alignment and successful program execution
• Clearly communicate scientific strategy, risks, data interpretations, and recommendations to project teams, leadership, and internal/external partners
• Maintain thorough and timely documentation in electronic laboratory notebooks and company systems
• Author technical reports, protocols, and presentations for internal and external audiences

Qualifications & Requirements:

• Education and Experience:
  • PhD or equivalent experience in phycology, plant biology, molecular biology, biochemistry, molecular biology, microbiology, chemistry, or related field
  • Minimum of five years’ experience with biochemistry, microbiology, or molecular biology
  • Demonstrated expertise with upstream or downstream process modeling for biologics
  • Experience with multi-factor Design-of-Experiments (DOE), data analysis, and troubleshooting skills
  • Experience culturing microorganisms at research, pilot, and commercial scale preferred
  • Hands-on experience or the desire to learn biochemical and immunoassays (ELISA, MSD, SDS-PAGE, western blot, etc.), spectroscopic or fluorescence-based techniques, or quantitative PCR protocols
• Skills and Attributes:
  • Excellent organizational skills with meticulous attention to detail
  • Ability to manage multiple priorities and deliver high-quality results on time
  • Resourceful with proven ability to lead, manage, and leverage internal and external resources to plan and resolve issues
  • Strong interpersonal and collaborative skills to promote team success
  • Effective written and verbal communication skills, including the ability to explain complex technical concepts clearly
  • Demonstrated integrity, sound scientific judgement, and professional ethics
  • Ability to work both independently and in a highly collaborative team environment

Physical Requirements:

• Ability to work on-site in Seattle, WA
• Ability to sit/stand for extended periods of time (2 or more hours)
• Occasionally lift or carry up to 23 kg
• Perform delicate manual procedures in the laboratory.

Benefits at Lumen Bioscience:

• Stock bonus
• Health, Dental, and Vision premiums fully covered by Lumen
• 401k match up to 4%
• Industry-leading PTO policy, paid refresh days, and paid year-end holiday office closure
• Monthly wellness program to support your health and well-being
• Free onsite parking or public transportation subsidies
• Comprehensive parental leave policies
• Life insurance, short & long-term disability, and access to employee assistance programs

At Lumen Bioscience, we foster a workplace built on collaboration, innovation, and professional growth. This role offers a significant opportunity to contribute directly to cutting-edge biotechnology and the advancement of global health solutions.

Join us to shape innovative solutions and drive operational excellence.

About the Team

Our team is organized around the north star goal of building an AI scientist – a system capable of solving the long term reasoning challenges and basic capabilities necessary to push the scientific frontier. Our team likes to think across the whole model stack. Currently the team is focused on improving models' abilities to use computers – as a laboratory for long horizon tasks and a key blocker to many scientific workflows.

About the role

As a Research Engineer on our team you will work end to end, identifying and addressing key blockers on the path to scientific AGI. Strong candidates should have familiarity with language model training, evaluation, and inference, be comfortable triaging research ideas and diagnosing problems and enjoy working collaboratively. Familiarity with performance optimization, distributed systems, vm/sandboxing/container deployment, and large scale data pipelines is highly encouraged.

Join us in our mission to develop advanced AI systems that are both powerful and beneficial for humanity. 

Responsibilities: 

• Working across the full stack to identify and remove bottlenecks preventing progress toward scientific AGI
• Develop approaches to address long-horizon task completion and complex reasoning challenges essential for scientific discovery
• Scaling research ideas from prototype to production
• Create benchmarks and evaluation frameworks to measure model capabilities in scientific workflows and computer use
• Implement distributed training systems and performance optimizations to support large-scale model development

You may be a good fit if you:

• Have 8+ years of ML research experience
• Are familiar with large scale language model training, evaluation, and inference pipelines
• Enjoy obsessively iterating on immediate blockers towards longterm goals
• Thrive working collaboratively to solve problems
• Have expertise in performance optimization and distributed computing systems
• Show strong problem-solving skills and ability to identify technical bottlenecks in complex systems
• Can translate research concepts into scalable engineering solutions
• Have a track record of shipping ML systems that tackle challenging multi-step reasoning problems

Strong candidates may also have:

• Expertise with performance optimization for language model inference and training
• Experience with computer use automation and agentic AI systems
• A history working on reinforcement learning approaches for complex task completion
• Knowledge of containerization technologies (Docker, Kubernetes) and cloud deployment at scale
• Demonstrated ability to work across multiple domains (language modeling, systems engineering, scientific computing)
• Have experience with VM/sandboxing/container deployment and large-scale data processing
• Experience working with large scale data problem solving and infrastructure
• Published research or practical experience in scientific AI applications or long-horizon reasoning

Your Impact

We are seeking a skilled and innovative Senior Research Scientist to join one of our AI teams focusing on computer vision and machine learning (CVML). As a research scientist at Axon you will play a crucial role in developing AI solutions that transform both the enterprise and public safety domains and support our company’s mission: accelerate justice, protect truth, and save lives. You will advance the state-of-the-art in CVML and multimodal technology and apply your research findings to create new responsible AI capabilities for Axon products. You will collaborate with product managers, engineers and cross-functional teams to train models and develop cutting-edge algorithms and solutions that enable intelligent perception and understanding of visual data.

At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

What You’ll Do

Reports to: Director of AI Research
Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

• Collaborate with other scientists, engineers and product managers to build proof-of-concepts to shape the Axon of tomorrow.
• Lead end-to-end research efforts in advanced computer vision, machine learning and gen-AI techniques for cloud and devices from multimodal data sources, including scene understanding, action recognition and anomaly detection.
• Design and implement responsible, privacy-preserving, efficient and scalable models for inference and analysis of visual data.
• Develop performance and quality metrics for CVML models and systems, and validate their effectiveness in real-world settings.
• Optimize algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
• Stay up-to-date with the latest research and advances in CVML and translate relevant findings into shipping Axon products.
• Contribute to academic publications, technical documentation, and patent disclosures to share insights and findings with the broader community.
• Coach and mentor junior scientists.

What You Bring

• PhD and 3+ years experience in Computer Science or a related field with a focus on computer vision, machine learning, artificial intelligence or related technical fields.
• Proven track record of research in machine learning, computer vision or related fields.
• Experience driving the ML development lifecycle and leveraging state-of-the-art research to deliver high quality models at scale.
• Strong computer vision fundamentals such as image processing, feature extractions, object detection, semantic segmentation, video analysis or action recognition.
• Excellent problem-solving skills, analytical thinking, and the ability to work independently as well as collaboratively in a team environment.
• Proficiency in Python and frameworks such as PyTorch, TensorFlow or Keras.
• Strong communication skills and the ability to effectively present complex technical concepts to both technical and non-technical audiences.
• Experience in developing computer vision algorithms for resource-constrained edge devices or embedded systems preferred but optional.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, Dental, Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work

The Pay: Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The starting base pay for this role is between USD 159,750 in the lowest geographic market and USD 234,300 in the highest geographic market. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit www.axon.com/careers/benefits.

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