Do you consider yourself a self-starter with a real passion for projects involving innovative methods in evidence synthesis? Do you love collaborating, moving the ball forward and rolling up your sleeves? We are growing and seeking a Senior Research Scientist with technical experience in systematic literature reviews and/or indirect treatment comparisons (e.g. NMA, MAIC, STC) for the purposes of health technology assessment submissions. We offer opportunities to work 100% remotely from Canada or the US.

Our culture is similar to that of a start-up, but in a well-funded established global portfolio organization. We pride ourselves on being leaders with vision in our field! Below are some examples of recent work we have published as part of our efforts to support our clients:

• Cope S, Chan K, Jansen JP. Multivariate network meta‐analysis of survival function parameters. Research synthesis methods. 2020;11(3):443-456. https://doi.org/10.1002/jrsm.1405

• Freemantle N, Xu Y, Wilson FR, et al. Network meta-analysis of immune-oncology monotherapy as first-line treatment for advanced non-small-cell lung cancer in patients with PD-L1 expression ≥50. Ther Adv Med Oncol. 2022; 14:17588359221105024. https://doi.org/10.1177/17588359221105024
• Watts, JM, Wang, ES, Jonas, BA, Wilson FR, et al. Matching-Adjusted Indirect Comparison of Olutasidenib and Ivosidenib in Isocitrate Dehydrogenase 1-Mutated Relapsed/Refractory Acute Myeloid Leukemia. Adv Ther. 2026;43:1802–1815. https://doi.org/10.1007/s12325-026-03522-6
• Keeping ST, Cope S, Chan K, et al. Comparative effectiveness of nivolumab versus standard of care for third-line patients with small-cell lung cancer. J Comp Eff Res. 2020;9(18):1275–1284. https://doi.org/10.2217/cer-2020-0134

Senior Research Scientists collaborate across a broad portfolio of sophisticated evidence synthesis projects in a multi-level team structure. Responsibilities include development of deliverables (e.g. study protocols and technical reports), handling day-to-day client communications, as well as delegating and overseeing tasks completed by junior researchers. This position will complete complex job responsibilities independently as well as provide mentorship and direction for others in delivering project work.

Essential functions for this role are:

• Subject Matter Expertise/Domain Knowledge
• Demonstrates understanding of the pharmaceutical industry, medical affairs, and requirements for health technology assessments
• Sufficient understanding of relevant methods to be able to oversee systematic literature reviews (clinical, economic, and/or health-related quality of life) and/or quantitative evidence synthesis studies
• Can identify considerations relevant to the synthesis of available evidence and communicate these within deliverables (e.g., feasibility assessments, statistical analysis plans)
• Deliverable Creation
• Develops client-ready deliverables including protocols, statistical analysis plans, technical reports, and slides
• Strategic Direction
• Contributes to short-term resourcing discussions
• Project Management
• Manages the delivery of components of projects by collaborating with other staff members to ensure high quality outputs
• Helps ensure timely delivery and financial performance of projects or project subcomponents
• Estimates required hours and identifies challenges early on and communicates any changes as well as viable solutions to project lead if necessary
• Client Management
• Reviews update slides/minutes and actions for overall study and viewed by client as independent researcher for specific study or component(s)
• Leads client calls and responds to emails, inviting input from senior team members with methodological/subject matter expertise where appropriate
• Line Management/Team Development
• Creates development plans and acts as a mentor for direct reports
• Business Development
• Contributes to development of proposals and presentations under guidance of more senior team members with methodological/subject matter expertise
• May also participate in meetings related to new business, including concept ideation

Minimum required experience for this role is:

• Master’s degree in a subject related to health services research e.g., health economics, public policy, health policy, epidemiology, biostatistics, public health, or science (biology/biochemistry etc.)
• 4-6 years’ professional experience

 Core competencies required for this role are:

• Willingness and desire to learn and share knowledge
• Excellent oral and written communication skills
• Proficiency with Microsoft Office and EndNote
• Proficiency in R/R Shiny advantageous

#LI-TB1

#LI-Remote

We’re looking for a Senior Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Develop impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Be part of a client-facing team that finds, defines, and solves problems of real-world interest using IonQ trapped-ion quantum computers.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• Hands-on expertise with using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• Demonstrated experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1360

We are looking for a Staff Scientist – Fault-Tolerant Quantum Algorithms to lead the technical development in utilizing IonQ’s quantum computers to create highly differentiated quantum solutions that will bring value to society. As a Staff Scientist – Fault-Tolerant Quantum Algorithms, you’ll be a core member of a cross-functional team whose mandate is central to IonQ’s mission to solve the world’s most complex problems using the world’s best quantum computers.

As a hands-on expert in fault-tolerant algorithms, you will help discover the next generation of quantum applications that are poised to deliver results exceeding state-of-the-art classical methods. You will play a key role in developing quantum algorithms, core IP, computational resource models, long-term roadmaps, and end-to-end workflows that have the potential to disrupt the field of computing. You will also work closely with product, engineering, marketing, sales, operations, and external customers/partners to brainstorm new ideas, propose complex, multi-year initiatives and represent IonQ at high-visibility technical conferences (often all in a single day)!

Responsibilities: 

• Lead hands-on development of novel fault-tolerant quantum algorithms that will make a large scientific and commercial impact across a wide range of industry verticals.
• Perform detailed resource analyses of quantum algorithms and perform SWOT analysis of FTQC approaches as compared to NISQ and/or classical methods.
• Provide trusted expertise in FTQC algorithms and communicate the current state-of-the-art, scaling behaviors, trade offs, cross-over points, etc. to stakeholders across the company.
• Drive constructive technical interactions across multi-disciplinary teams to identify, define and solve challenging real-world problems using IonQ trapped-ion quantum computers.
• Develop and drive adoption of industry-leading benchmarking and resource estimation methodologies, metrics, and tools.
• Develop portfolio of foundational IP and high-impact-factor peer-reviewed publications; represent IonQ externally with customer/clients and at conferences.

You’d be a good fit with:

• PhD in physics, mathematics, computer science, or similar field, or comparable field or equivalent work experience + 3 years of professional experience in the quantum computing field
• Demonstrated expertise in FTQC algorithms that can scale to millions of qubits, billions of gates with line-of-sight to end-customer value: active portfolio of invited talks, repos, licenses, publications and/or patents
• Active participant in the FTQC algorithm community via, e.g., development of tools (libraries, simulators, compiler), metrics (costing, resource estimation, ROI), and/or community (economic development, standards)
• Relentless dedication to optimizing algorithmic performance (accuracy, time-to-solution) through elegant theoretical equations, as well as engineering optimization 
• Mastery of key mathematical techniques used in quantum computing and quantum algorithm development, and a demonstrated ability to communicate scientific results clearly.

You’d be a great fit with: 

• 5+ years of professional work experience developing end-to-end solutions for realistic industry problems such as computer-aided engineering, cybersecurity, chemistry, etc.
• Experience working with quantum algorithms for relevant use cases. This could include quantum simulation (e.g., product formulas, qubitization, qDRIFT, etc.), quantum algorithms and primitives (e.g., block-encodings, LCU, QSP, QSVT, Gibbs sampling, quantum linear systems, etc.), and/or end-to-end fault-tolerant quantum algorithms as applied to detailed use cases.
• Demonstrated expertise in Python and Qiskit or similar quantum SDK; working knowledge of C++.
• Experience proposing, winning, and executing on consultative (paid) contracts; government contracting or defense contracting experience a plus
• Experience commercializing end-to-end software utilizing hybrid computing e.g. CPU + GPU + QPU, Edge, Cloud, etc. Knowledge of CI/CD a plus.

Location: This position can work onsite or hybrid from one of our offices (College Park, MD, Bothell, WA, Toronto, Canada, Gothenburg, Sweden) or fully remote in the US
Travel: 10% domestic and international
Job ID:  1058

The approximate base salary range for this position is $167,808 - $219,704. The total compensation package includes base, bonus, and equity.

We’re looking for a Staff Quantum Applications Scientist - Life Sciences who will be part of a cross-functional team at IonQ whose mission is to deliver the world’s best quantum solutions in life sciences on the world’s best quantum computers to solve the world’s most complex and impactful problems. This role is open as part of IonQ’s Quantum Applications team based in either Gothenburg, Sweden or Toronto, Canada. You will work closely with partners within the life sciences innovation ecosystem and beyond to create new hybrid quantum applications with significant commercial impact.

Responsibilities: 

• Originate and lead development of impactful hybrid quantum applications, algorithms and solutions in the life sciences domain that promise commercial advantages in practice and at scale.
• Collaborate with quantum compiler, cloud and hardware engineering teams to develop highly optimized hybrid workflows for trapped-ion quantum computers.
• Contribute knowledge of classical and quantum domain-specific algorithms and tools to evaluate and communicate pros and cons, current state-of-the-art, scaling behavior, trade offs, cross-over points, etc.
• Lead constructive technical interactions with client teams to find, define, and solve problems of real-world interest using IonQ trapped-ion quantum computers.
• Represent the team in client and stakeholder presentations, develop presentation content and appropriately adapt it to the audience.
• Build reusable software platforms to grow IonQ’s user base. Integrate first of a kind quantum algorithms into larger end-to-end workflows.

You’d be a good fit with: 

• Doctorate degree in the life sciences domain, or equivalent work experience.
• At least 3 years of professional experience using and developing computational and ML/AI tools in bioinformatics, molecular biology, development of advanced therapeutics, including a track record of peer-reviewed manuscripts and contributions to code bases.
• At least 3 years of professional experience developing, applying, validating quantum computing algorithms and solutions in the life sciences domain, including prototyping solutions using Python and quantum SDKs like Qiskit, PennyLane, Cirq.
• Desire to work closely with customers including aligning with time zones and work schedules. Potential for international travel and/or onsite co-location.

You’d be a great fit with:

• Expertise in key mathematical techniques used in quantum computing - linear algebra, matrix decompositions, probability theory, symmetry, computational complexity.
• Success working directly with clients to define and deliver solutions; excellent collaboration and communication skills.

Location: Onsite and/or hybrid from our office in Gothenburg, Sweden or Toronto, Canada
Travel: 10% domestic and international, with a focus on visiting customers and clients
Job ID: 1361

We are looking for a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms to help lead the technical development of highly differentiated quantum solutions that will bring value to society. As a Senior Staff Scientist – Fault-Tolerant Quantum Algorithms, you’ll guide a cross-functional team whose mandate is central to IonQ’s mission to solve the world’s most complex problems using the world’s best quantum computers.

As a technical leader in the field of fault-tolerant algorithms, you will help discover the next generation of quantum applications that will exceed state-of-the-art classical methods. You will be a core member of technical leadership in quantum algorithms, and you will drive research into new quantum algorithms and develop IP, computational resource models, long-term roadmaps, and end-to-end workflows that have the potential to disrupt the field of computing. You will also work closely with product, engineering, marketing, sales, operations, and external customers/partners to brainstorm new ideas, propose complex, multi-year initiatives and represent IonQ at high-visibility technical conferences (often all in a single day)!

Responsibilities: 

• Influence the quantum applications roadmap towards fault-tolerant quantum algorithms that will make a large scientific and commercial impact by leading the origination, execution, and optimization of novel, end-to-end quantum algorithms. Guide other team members towards this goal.
• Perform detailed resource analyses of quantum algorithms and perform SWOT analysis of FTQC approaches compared to NISQ and/or classical methods.
• Provide trusted expertise and leadership in FTQC algorithms and communicate the current state-of-the-art, scaling behaviors, trade offs, cross-over points, etc. to stakeholders across the company.
• Lead technical interactions across multi-disciplinary teams to identify, define and solve challenging real-world problems using IonQ trapped-ion quantum computers.
• Define, develop, and drive adoption of industry-leading benchmarking and resource estimation methodologies, metrics, and tools.
• Develop portfolio of foundational IP and high-impact-factor peer-reviewed publications; represent IonQ externally with customer/clients and at conferences.

You’d be a good fit with:

• PhD in physics, mathematics, computer science, or similar field, or comparable field or equivalent work experience + 5 years of professional experience in the quantum computing field
• 13+ years of professional experience or an equivalent combination of education and experience
• Demonstrated expertise in FTQC algorithms that can scale to millions of qubits, billions of gates with line-of-sight to end-customer value: active portfolio of invited talks, repos, licenses, publications and/or patents.
• Active participant in the FTQC algorithm community via, e.g., development of tools (libraries, simulators, compiler), metrics (costing, resource estimation, ROI), and/or community (economic development, standards)
• Relentless dedication to optimizing algorithmic performance (accuracy, time-to-solution) through elegant theoretical equations, as well as engineering optimization
• Mastery of key mathematical techniques used in quantum computing and quantum algorithm development, and a demonstrated ability to communicate scientific results clearly.

You’d be a great fit with: 

• 7+ years of professional work experience developing FT quantum algorithms that align with realistic industry problems such as computer-aided engineering, phase transitions, reaction modeling, cybersecurity, differential equations solving, simulation of physical systems, etc. 
• Deep expertise in quantum algorithms for relevant use cases. This could include quantum simulation (e.g., product formulas, qubitization, qDRIFT, etc.), quantum algorithms and primitives (e.g., block-encodings, LCU, QSP, QSVT, Gibbs sampling, quantum linear systems, etc.), and/or end-to-end fault-tolerant quantum algorithms as applied to detailed use cases.
• Demonstrated expertise in Python and Qiskit or similar quantum SDK; working knowledge of C++.
• Experience proposing, winning, and executing on consultative (paid) contracts; government contracting or defense contracting experience a plus
• Experience commercializing end-to-end software utilizing hybrid computing e.g. CPU + GPU + QPU, Edge, Cloud, etc. Knowledge of CI/CD a plus.

Location: This position can work onsite or hybrid from one of our offices (College Park, MD, Bothell, WA, Toronto, Canada, Gothenburg, Sweden) or fully remote in the US
Travel: 10% domestic and international
Job ID:  1254

The approximate base salary range for this position is $192,979 - $252,659. The total compensation package includes base, bonus, and equity.

PLEASE NOTE: This is a fully remote, 1099 independent contractor opportunity with an estimated duration of six months and the potential for extension. To be eligible, candidates must be authorized to work in Canada.

About the Program

The Human Frontier Collective (HFC) Fellowship brings together top researchers and domain experts to collaborate on high-impact work that are shaping the future of AI. As an HFC Fellow, you’ll apply your academic and professional expertise to help design, evaluate, and interpret advanced generative AI systems—while gaining exposure to cutting-edge research and working alongside an interdisciplinary network of leading thinkers.

What You'll Do

• ML Projects: Get invited to engage in high-impact projects with our partnered AI labs and platforms. Help models understand real-world deep learning workflows by designing, reviewing, and optimizing PyTorch models, evaluating complex ML code and AI-generated implementations for efficiency and correctness, and advising on GPU optimization, scaling, and trade-offs.
• HFC Community: Beyond the work, you’ll become part of a supportive, interdisciplinary network of innovators and thought leaders committed to advancing frontier AI across domains.
• Contribute to Research Publications: Collaborate with Scale’s research team to co-author technical reports and research papers—boosting your academic visibility and professional recognition (e.g., SciPredict, PropensityBench, Professional Reasoning Benchmark).

Who Should Apply

• Education: PhD or postdoctoral degree in Computer Science, Computer Engineering, or a related field.
• Professional Background: 1-3+ years of experience as a Machine Learning Engineer or Data Scientist.
• Skills: Strong proficiency in Python and modern ML frameworks (PyTorch, TensorFlow). Experience with cloud infrastructure (AWS) and MLOps tools (Docker, Langchain) is a plus.
• Professional Mindset: Detail-oriented, innovative thinker with a passion in applied AI research and a commitment to collaboration.

Why Join the HFC?

• Professional Development: High-impact experts expand their influence through review projects, advisory roles, and research, while deepening their AI expertise, strengthening analytical and problem-solving skills, and engaging with pioneering AI applications in science and technology.
• Join a Top-Tier Network: Collaborate with a global network of engineers and experts to advance responsible AI through impactful, flexible research and training. 80% of our members come from leading institutions.
• Flexible Schedule: Set your own schedule, with flexible 10–40 hour weeks that fit around your life and other commitments.
• Competitive Pay: Project pay rates vary across platforms and are depending on a number of factors, including but not limited to; projects, scope, skillset, and location. 

Application Process

1. Apply: We review applications on a rolling basis.
2. Interview: Candidates will get to discuss their research experience, professional background, and alignment with our mission to advance human-centered AI.
3. Join the Collective: Successful candidates will receive an invitation to join the Human Frontier Collective Fellowship.

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads targeting, relevance modeling, auction optimization, measurement, and user experience. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Data Scientist to join our growing Ads Data Science team. As a Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve our understanding of the dynamics that drive the success of our advertising platform, and identify opportunities to accelerate that success. You will work closely with stakeholders across product, engineering, sales, marketing, and data to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Develop ML models & DS methods to for improved anomaly detection, prediction, pattern recognition
• Communicate findings and recommendations to stakeholders across the organization
• Collaborate with product, engineering, sales, and marketing partners to define product and program requirements and translate them into data science solutions
• Stay up-to-date on the latest advancements in machine learning and data science

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 3+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 2+ years of industry experience in applied science or data science roles
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

We are looking for a highly motivated and experienced Senior Data Scientist to join our growing Ads Data Science team. As a Senior Data Scientist, you will play a key role in developing as well as applying cutting-edge DS models/methods to improve the adoption and performance of our advertising platform through data-driven insights. You will work closely with product managers, engineers, and other data scientists to identify opportunities, define metrics, and build solutions that drive significant impact for Reddit.

Responsibilities:

• Design, develop, and apply DS solutions to inform improvements in advertiser experience and Reddit's ad platform
• Analyze large-scale datasets to identify trends, patterns, and insights that can be used to improve the effectiveness of our advertising platform
• Collaborate with product managers and engineers to define product requirements and translate them into data science solutions
• Develop ML models & DS methods to improve anomaly detection, prediction, & pattern recognition 
• Communicate findings and recommendations to stakeholders across the organization
• Stay up-to-date on the latest advancements in machine learning and data science
• Mentor and guide junior data scientists on the team

Qualifications:

• Advanced degree (Masters or Ph.D.) in a quantitative field such as: Statistics, Mathematics, Physics, Economics, or Operations Research
• For M.S. holders: 5+ years of industry experience in applied science or data science roles
• For Ph.D. holders: 4+ years of industry experience in applied science or data science roles
• Platform experience and a deep understanding of the ads ecosystem
• Strong understanding of statistical modeling, machine learning algorithms, causal inference and experimental design
• Experience with large-scale data processing and analysis using tools such as Spark, Hadoop, or Hive; knowledge of BigQuery a plus
• Proficiency in Python or R and experience with machine learning libraries such as scikit-learn, TensorFlow, or PyTorch
• Experience with SQL and relational databases
• Excellent communication and presentation skills
• Passion for Reddit and the online advertising industry

Bonus Points:

• Experience with online advertising and ad tech
• Experience with causal inference and A/B testing
• Contributions to open-source projects or publications in relevant conferences or journals

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be.

Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business.

About the Ads Data Science Team:

The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. 

We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling.

About the Role:

Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality.

This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization.

Responsibilities:

• Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy.
• Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers.
• Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS.
• Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.
• Lead Through Cross-Functional and Technical Influence: Collaborate deeply with engineering, product, and sales to align on strategic goals, translate insights into action, and drive execution. Set a high technical bar by mentoring others and championing best practices across modeling, experimentation, and measurement.

Qualifications:

• Required:
  • Advanced degree (Master's or Ph.D.) in Statistics, Mathematics, Physics, Economics, or Operations Research
  • For M.S. holders: 10+ years of industry experience in applied science or data science roles
  • For Ph.D. holders: 6+ years of industry experience in applied science or data science roles
  • Deep understanding of the ads ecosystem
  • Demonstrated expertise in at least one of the following areas:
    • Measurement & Experimentation at Scale (with focus on lift and attribution)
    • Identity Graph Creation & Resolution Methodology and Infrastructure
    • Predictive Modeling with Signal Loss
  • Advanced proficiency in statistical programming (Python or R) and SQL
  • Experience with machine learning or optimization techniques
  • Strong understanding of experimental design, causal inference, or A/B testing methodologies
  • Exceptional problem-solving and communication skills, with a track record of influencing product and engineering partners
  • Experience working in fast-paced, ambiguous environments with cross-functional teams

Benefits:

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
• Family Planning Support
• Gender-Affirming Care
• Mental Health & Coaching Benefits
• Comprehensive Medical Benefits & Health Care Spending Account
• Registered Retirement Savings Plan with matching contributions
• Income Replacement Programs
• Flexible Vacation & Paid Volunteer Time Off
• Generous Paid Parental Leave

#LI-Remote

What do we need

We are seeking a Scientific Technical Solutions Lead to join the team developing scientific Solutions built on Dotmatics LUMA, a next-generation, multi-tenant, AI-powered data management and workflow automation for multimodal scientific discovery. As a Scientific technical lead on the team, you will work closely with other Solution Architects, product management, engineering teams, and external stakeholders to deliver exceptional product capabilities via Luma Solutions.

Your focus will be on designing and implementing the configuration necessary to realise product vision and on ensuring that this configuration follows best practices within the Life Sciences and Chemical & Material space.

This role offers the opportunity to shape a foundational part of the modern lab—helping scientists work faster, smarter, and with greater impact.

In this role you will get to:

• Design configuration: Collaborate with Product to determine application structure, define entity/data models, specify task workflows (Scientific Workflows) , and define desired data visualization experiences
• Develop configuration: Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions that will be delivered as part of the product
• Test and troubleshoot configuration: Perform in-team testing of configuration and assist is handing test cases to the QA group for release testing. Troubleshoot configuration to understand why it is not producing desired results.
• Contribute to documentation: Write draft documentation of configuration and workflows and collaborate with the Documentation team to develop final customer-facing documentation
• Train internal and external users: Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports
• Provide input into new product features: Use new product features in Luma Solutions and provide feedback on the experience, participate in user experience testing, and provide input to the Product team about features that will enable the best Solutions
• Champion quality and best practices: Actively participate in the development of best practices for Luma configuration, and ensure these best practices are followed in the development of Luma Solutions

We are looking for people who have 10+ years of hands-on experience building and delivering informatics solutions for Life Sciences customers. The ideal candidate holds a Bachelor's or advanced degree in Life Sciences, Data Science, Chemistry, Biology, Bioinformatics, or a related technical discipline — and brings a genuine passion for quality and continuous improvement, fueled by a drive to solve problems that truly matter.

The key skills we are looking for: 

• Life Science Industry experience, either as a Scientific Solution Architect, technical application Scientist or a Scientist who has been heavily involved with designing products or technical applications
• Advanced expertise in data modeling, with a proven ability to design robust, scalable data structures
• Expert-level proficiency in configuring low-code platforms and designing end-to-end workflows
• Demonstrated success delivering scientific data platforms or tools spanning data modeling, ETL, APIs, and BI/reporting
• Expert-level SQL skills, with strong working knowledge of Python and JSON
• Deep experience integrating tools and modules to architect complete, cohesive solutions
• Strong analytical ability to translate product requirements into precise technical configuration designs
• Excellent communication skills — able to distill complex technical concepts for both technical and non-technical audiences at all levels
• Experience running and/or supporting scientific workflows in a production or research environment

You may also have 

• Experience running scientific test cases
• Understanding of software testing and or SDLC
• Working knowledge of Databricks
• Drug Discovery or Biotechnology industries or Other scientific Industries

The Growth Tech Alliance's goal is to enable HelloFresh to drive smarter marketing through AI-powered automation, intelligent systems, and advanced optimization. We've pioneered cutting-edge approaches to programmatic campaign optimization using state-of-the-art AI/ML technologies and are now scaling these capabilities across our global marketing operations. Our team’s key responsibilities include designing, building, maintaining autonomous decision-making systems, advanced ML models for marketing optimization, and real-time intelligence that drives measurable business impact. We work at the intersection of modern AI architectures, deep statistical modelling, and enterprise-scale ML operations.

S'more about the team

As a Senior Data Scientist in AdTech, you will design, build, and deploy production-grade machine learning models that drive significant marketing ROI. You will provide critical expertise in advancing our intelligent marketing optimization systems, focusing on the entire ML lifecycle from data preprocessing and feature engineering to large-scale deployment and performance monitoring. By translating complex marketing challenges into robust production systems, you will ensure our AI-driven capabilities deliver measurable business impact and enhanced efficiency at a  global scale

Lettuce share what this role will be responsible for

• Develop, build, and iterate on advanced machine learning models across core adtech domains to optimize marketing performance and contribute to the orchestration of highly efficient marketing workflows.
• Design and implement ML models for Media Optimization, and contribute to their operationalization into high-impact production systems.
• Contribute to Creative Automation efforts by building and enhancing predictive AI models to guide our global production studios.
• Design and build ML models for Value Optimization to intelligently isolate high-value customers.
• Adhere to and contribute to the team's ML operations (MLOps) practices, focusing on experiment tracking, system observability, and model reliability in production.
• Rapidly prototype innovative machine learning solutions, including Gen AI-forward approaches, and integrate them into our existing, orchestrated multi-agent systems to enable complex autonomous workflows.
• Collaborate closely with Product, Engineering, and Marketing to identify high-impact programmatic automation opportunities and execute robust A/B testing and experimentation designs for models in high-noise environments.
• All other duties, as assigned

Sound a-peeling? Here's what we're looking for

• MSc or equivalent experience in a quantitative discipline with proven experience building and deploying AI/ML systems from prototype to production at scale
• Expert proficiency in Python, PySpark, and SQL, hands-on experience with cloud environments (GCP, AWS, or Azure), and practical experience with modern machine learning frameworks such as HuggingFace, TensorFlow or similar.
• Expertise in applied machine learning relevant to AdTech, including predictive modeling, optimization algorithms, and modern LLM capabilities preferred.
• Proven experience tackling complex marketing data problems, such as algorithmic budget pacing, LTV prediction pipelines, or AI-driven media optimization systems.
• Strong foundation in statistical analysis and experimentation, with practical experience designing A/B tests to validate the incremental business impact of algorithmic systems
• Demonstrated ability to effectively communicate intricate analytical findings to diverse audiences, bridging the gap between deep technical implementation and core business KPIs
• Track record of building production ML systems with robust practices, demonstrating a bias for action and extreme ownership, treating the business outcomes of your algorithms with a true Founder Mentality
• Experience with programmatic advertising ecosystems, marketing analytics, and the operational aspects of running performance-critical ML models in high-traffic environments

Let’s cut to the cheese, this is why you'll love it here

• Box Discount - Amazing discounts on 1 box per week! 75% discount on weekly HelloFresh and Chefs Plate meal kits AND 50% off weekly Factor meal box.
• Health & Wellness - Health & Dental benefits from day 1, a Health Spending Account, unlimited access to the Headspace app to meet your self-care needs, and 25% discount on GoodLife fitness memberships!
• Vacation & PTO - Time off is also an important part of self-care! We offer generous vacation and PTO to help you create a good work-life balance. 
• Family Benefits - A parental leave top-up program for expectant parents.
• Growth & Development - We support your career progression and invest in your continued learning through experiences and initiatives owned by our dedicated L&D team
• Work Hard & Have Fun - From team socials to engaging company days, you’ll have plenty of opportunity to experience the fun!
• Diversity & Inclusion Initiatives - With impactful ERG’s like FreshPride, Women Empowered and LIMES, we are committed to our diversity, equity & inclusion efforts.
• Food Puns - this one is kind of a big dill if you haven’t already noticed. We even have some punny meeting room names!

Flexible Hybrid Approach

At HelloFresh, we know that flexible work arrangements are essential in enabling you to do your best work, while balancing your personal and life needs. Offering remote work flexibility, along with the opportunity to interact and collaborate in the office are all a part of creating a great employee experience. 

To meet these needs, we are pleased to provide Flexible Hybrid work. Flexible Hybrid is a people-first approach that is based on choice, trust, personalization, and empowers teams to choose when and how often they work from the office and work from home, in addition to team days and company days. This means a minimum of 2 days in office per week, with most teams in office between 2-3 days a week.

#LI-HYBRID

HelloFresh Canada uses AI-integrated technology to help us process and evaluate applications more efficiently. This includes tools that screen and assess candidate qualifications based on the requirements for this role. While these tools assist our workflow, all final selection decisions are made by our hiring team.

This is a posting for an existing vacancy. We are actively seeking to fill this position.

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.

The Fraud Data Science team safeguards Robinhood and its customers by detecting and preventing fraud and abuse across our platform. We leverage machine learning and analytics to combat malicious behavior in real time, supporting a safe and trusted experience for all users. Our work has a direct impact on customer security, company risk posture, and regulatory compliance.

As a Senior Data Scientist on the Fraud team, you will own the design and deployment of ML solutions that proactively surface suspicious activity, reduce financial loss, and improve fraud detection precision. You’ll collaborate closely with engineering, product, risk, and compliance partners to influence system architecture, shape policy through data, and enhance the safety and integrity of our platform.

This role is based in our Menlo Park office, with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Design and deploy fraud detection models to protect Robinhood users and assets in real time
• Analyze behavioral data to uncover emerging fraud vectors and support rapid incident response
• Develop robust data pipelines and monitoring systems to ensure model accuracy and reliability
• Partner with engineering and product teams to implement safeguards and user-facing features
• Guide experimentation strategy and contribute to long-term fraud prevention roadmap

What you bring

• 5+ years of experience in data science or applied ML, with a focus on fraud detection or risk mitigation
• Advanced proficiency in Python and SQL; experience with ML frameworks like XGBoost, LightGBM, or TensorFlow
• Strong statistical acumen with experience in anomaly detection, pattern recognition, and A/B testing
• Excellent communication skills and ability to influence decision-making across technical and non-technical audiences
• A collaborative mindset and proactive approach to navigating ambiguity in fast-paced environments

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

About the Job

Do you get excited when a messy, ambiguous business problem finally yields to the right model? Do you think in systems, speak fluently across the technical-business divide, and want your work to do more than sit in a notebook — you want it to actually ship, scale, and matter?

With over 2,000 employees, 36 offices on five continents, and world-class clients like Samsung, L'Oréal, and Mattel, Artefact is a consulting firm that transforms data into measurable value and business impact. We're growing our Canadian presence and want you to join us as a technical cornerstone of our founding team in Canada.

Who We Are

Founded and headquartered in Paris, Artefact is a next-generation consulting firm specializing in data, analytics, and AI consulting — dedicated to transforming data into business impact across the entire value chain of organizations. We don't just advise; we build, implement, and deliver results our clients can measure.

We have 2,000 employees across 36 offices focused on accelerating digital transformation for some of the world's most recognizable brands. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of elite business consultants, data analysts, data scientists, data engineers, and digital experts are all laser-focused on delivering real value to every client. We design data-driven solutions tailored to each client's specific needs — always conceived with a business-first mindset and delivered with tangible, measurable results. Our expertise is built on deep AI knowledge acquired through 1,000+ client engagements across the globe.

Find out more at artefact.com.

What You Will Be Doing

As a Senior Data Scientist, you'll be the technical engine behind some of our most complex and consequential client engagements in Canada. You'll move fluidly between data exploration, model development, and executive communication — bringing scientific rigor to business problems and translating results into strategies that clients actually implement.

This isn't a role where you hand off findings and walk away. You'll be embedded with clients across Canada's most dynamic sectors — financial services, retail, CPG, telecoms, media, and the public sector — co-owning outcomes and ensuring that the models you build don't just perform in a test environment, they create real, lasting impact in production. You'll also be a technical anchor for our Canadian team, setting standards, mentoring junior data scientists, and contributing to the methodologies that define Artefact's edge in this market.

Key responsibilities include:

• Designing and building end-to-end machine learning and statistical models that solve high-stakes business problems — from framing the question to deploying the solution
• Conducting rigorous exploratory data analysis to uncover patterns, anomalies, and opportunities that inform both technical and strategic decisions
• Translating complex model outputs and analytical findings into clear, compelling narratives for senior client stakeholders — making the technical accessible without dumbing it down
• Partnering with client teams and data engineers to ensure models are production-ready, scalable, and built on clean, reliable data pipelines
• Defining the analytical approach for client engagements — selecting the right methods, tools, and frameworks for the problem at hand, not just the ones you're most comfortable with
• Contributing to new business proposals — helping articulate Artefact's technical capabilities and translating data science into clear client value
• Developing thought leadership and internal methodologies — publishing research, building reusable frameworks, and raising the technical bar across the Canadian practice
• Mentoring junior data scientists and analysts, actively investing in the team's technical depth and growth

What We Are Looking For

We want someone who is as comfortable whiteboarding a modeling strategy with a client's Chief Analytics Officer as they are debugging a pipeline before a critical delivery. You've shipped models that people actually use. You've sat in rooms where the business stakes were real, and you've delivered. You know the difference between a technically elegant solution and a practically useful one — and you always choose useful.

You'll arrive ready with the following:

• 4–7 years of hands-on experience in data science, machine learning, or advanced analytics — with a demonstrable track record of end-to-end model delivery in a client-facing or high-stakes business environment
• Advanced degree (MSc or PhD) in a quantitative field — statistics, mathematics, computer science, engineering, or equivalent; strong undergraduate candidates with exceptional experience will be considered
• Expert-level proficiency in Python and/or R; you write clean, maintainable, production-quality code
• Deep expertise in machine learning and statistical modeling — regression, classification, clustering, time series, NLP, recommendation systems, and/or deep learning, depending on your specialization
• Strong command of SQL and experience working with large-scale datasets across cloud platforms (GCP, AWS, or Azure)
• Experience with MLOps practices — model versioning, monitoring, deployment pipelines, and productionization — is a significant differentiator
• Exceptional communication skills — you can explain a gradient boosting model to a CFO and a business case to an ML engineer, and both conversations land
• Demonstrated ability to lead technical workstreams and mentor junior team membersBilingualism (English/French) is a significant asset, particularly for client engagement in Quebec and federal government contexts
• Consulting or client-facing experience is highly desirable; the ability to manage ambiguity, scope problems, and deliver under pressure is essential
• Familiarity with Canada's data privacy regulatory landscape — PIPEDA, Quebec's Law 25, and sector-specific frameworks in financial services and healthcare — is a meaningful differentiator
• Exposure to marketing analytics, customer analytics, fraud detection, risk modeling, or demand forecasting within Canadian financial services, retail, or CPG is a strong asset

Why You Should Join Us

At this level, you're not just looking for a job — you're looking for the right environment to do your best work. Here's what makes Artefact different:

Variety that keeps you sharp. In a product role, you go deep on one problem. Here, you'll work across Canada's most dynamic industries and business functions — building the kind of range that makes exceptional data scientists truly exceptional. No two engagements are the same.

Your work actually ships. We have a relentless focus on adoption and impact. The models you build are designed from day one to live in production, influence decisions, and create measurable value — not to gather dust in a final report.

A global technical community, with local roots. With 2,000 data and AI specialists across 36 offices worldwide, you'll have access to some of the most sophisticated data science thinking on the planet — while building something meaningful right here in Canada. You'll bring global best practices to the Canadian market and contribute Canadian insights back to the world.

Founding team energy. We're building our Canadian practice, which means the standards, culture, and technical identity you help create now will define Artefact in this market for years to come. That's a rare opportunity at any stage of a career.

We are united by our values and strengthened by our hybrid expertise:

There is always a way — We're builders, diggers, and makers. Ideas only count if they get executed.
Client trust is won in the field — We show up where it matters, working side by side with our clients to solve what's real.
If not used, it is useless — We build for adoption and impact. True brilliance is measured by what changes, not what's delivered.
If not shared, our work is not done — Sharing knowledge is how we close the loop — for our clients and for each other.
We learn every day — In a field moving at the speed of light, intellectual curiosity isn't optional. It's survival.

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies for Dash Chat and Search
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies for Dash Chat and Search
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Preferred Qualifications

• Experience in startups or building 0→1 products
• Expertise in using data to inform AI/ML product development
• Background in SaaS product

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

We're looking for a Data Scientist to partner with product, engineering, and design teams to answer key questions about how to grow revenue, optimize product, scale and monetize the business, and launch high-impact initiatives. We solve challenging problems and boost business growth through a deep understanding of user behaviors with applied analytics techniques and business insights. An ideal candidate should have robust knowledge of consumer lifecycle and behavior analysis, customer segmentation, digital campaigns, monetization analytics and business operations for a SaaS company.  

Responsibilities

• Develop a deep understanding of customer journey phases and key business metrics
• Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments
• Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights
• Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes 
• Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends. 
• Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets 
• Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments
• Translate complex concepts into implications for the business via excellent communication skills, both verbal and written
• Understand what matters most and prioritize ruthlessly
• Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 3-5 years experience using analytics to drive key business decisions; examples include business/product/marketing analytics, business intelligence, strategy consulting
• Proven track record of being able to work independently and proactively engage with business stakeholders with minimal direction
• Significant experience with SQL and large unstructured datasets such as Hadoop
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Solid background in running multivariate experiments to optimize a product or revenue flow
• Strong verbal and written communication skills
• Proficiency in programming/scripting and knowledge of statistical packages like R or Python is a plus

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

Role Description

How many times do you get the opportunity to be on the ground floor of a big and important mission? What if you could be one of the top contributors defining the mission, guiding our teams, and influencing the direction of Dropbox’s AI-first journey? As a Senior Data Scientist for this new division, you will get to do exactly that. You will join a team of top-tier data scientists and become an integral part of the product organization, helping to scale this new business.

Joining on the ground floor of this startup team, you’ll partner directly with Data Science, Product, Engineering and Design leadership to shape the product roadmap, foster a top-tier, data-informed culture, and drive real AI/ML impact and execution along the way!

Responsibilities

• Partner with Product Engineers and Data Engineers to build the reliable, efficient, and scalable data foundations, tools, and processes to drive our AI/ML capabilities’ long-term growth
• Leverage data-driven insights to proactively identify most impactful opportunities, and directly influence product roadmaps and strategies
• Perform exploratory and deep-dive analysis to understand user workflows and engagement patterns on AI features, propose hypothesis, and design & execute experiments with great rigor and efficient data techniques
• Translate complex data insights into implications and recommendations for the business via excellent communication skills, both verbal and written
• Identify what matters most and prioritize ruthlessly for the area you will own
• Contribute to a culture of strong technical ownership, partner with DS leadership to keep evolving DS working model and elevate DS impact
• Work with cross-functional teams (including Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

Requirements

• Bachelors’ or above in quantitative discipline: Statistics, Applied Mathematics, Economics, Computer Science, Engineering, or related field
• 7+ years experience of leveraging data-driven analysis to influence product roadmap and business decision, preferably in a tech company
• Proven track record of being able to work independently, driver measurable business impact, and proactively engage with business stakeholders with minimal direction  
• Proficiency in SQL, Python or other programming/scripting languages
• Deep understanding of statistical analysis, experimentation design, and common analytical techniques like regression, decision trees
• Ability to provide data insights and recommendations for 0→1 product even when sample size is small
• Strong verbal and written communication skills

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.

As a Data Scientist on the Mapping team, you will collaborate with our world class team of engineers, product managers, and designers to grow and improve the quality of recommended routes and accuracy of our travel time estimations. We're looking for a passionate, driven Data Scientist who is excited to dive into our spatial data and build a best-in-class mapping product that provides safe, efficient, and seamless navigation for our rideshare drivers.

Data Science is at the heart of Lyft’s products and decision-making. You will leverage data and rigorous, analytical thinking to shape our mapping products and make business decisions that put our customers first. This will involve identifying and scoping opportunities, shaping priorities, recommending technical solutions, designing experiments, and measuring the impact of new features. You will help us solve some of the most impactful problems in mapping, including:

• How do we improve the quality of our map data in order to improve our recommendations?
• How do we benchmark and measure the success of our services?
• How do we validate features of the real world that affect our routing algorithms?
• Are we meeting our travel estimation promises to our customers?

Responsibilities

• Leverage data and analytic frameworks to identify opportunities for growth and efficiency
• Partner with product managers, engineers, and operators to translate analytical insights into decisions and action, and implement products to drive business goals
• Define and implement decision frameworks, measurement strategies, and scientific methodologies that bring consistency and rigor to business decisions and forecasts, balancing opportunity and uncertainty
• Deliver integrated, high-quality analytical outputs spanning multiple projects while navigating ambiguity, cross-team dependencies, and open-ended scope
• Design and analyze online experiments; communicate results and act on launch decisions
• Establish metrics that measure the health of our products, as well as rider and driver experience
• Identify and drive impact and alignment, shaping product and business strategy through data-centric presentations 
• Contribute to the Science community (hiring, onboarding, documentation, knowledge-sharing, tooling improvements), helping make Decision Science at Lyft more effective and scalable

Experiences

• Degree in a quantitative field such as statistics, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience
• 3+ years experience in a data science role or analytics role
• Demonstrated ability to own multi-project analytical scopes with ambiguous problem definitions and cross-functional integration
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency in SQL - able to write structured and efficient queries on large data sets
• Experience in programming, especially with data science and visualization libraries in Python or R, and machine learning libraries such as PyTorch, TensorFlow, Keras
• Experience in online experimentation and statistical analysis, and communicating results and recommendations to senior stakeholders
• Strong communication, critical thinking, and prioritization skills, including the ability to challenge assumptions, propose alternatives, and balance short-term vs. long-term tradeoffs
• Experience in applying machine learning techniques is a plus (e.g. reinforcement learning) to solve customer problems (e.g. personalization, segmentation)
• Expertise in metric design, causal analysis, behavioral analytics, decision frameworks and measurement strategy is a plus
• Experience working with ETL pipelines a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 at least 3 days per week, including 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 Toronto area is $108,000 - $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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

The Safety & Customer Care (SCC) organization manages over 1.7 million monthly customer interactions and is responsible for ensuring the trust and safety of our riders and drivers. We work every day to build a trusted community, foster safe interactions, manage risky situations, and deliver best-in-class support. As part of this team, you will play a critical role in making transportation safer for all.

We are looking for an experienced and highly motivated Data Scientist to join the Community Safety Data team and lead key initiatives that enhance the safety of Lyft’s community. You’ll work cross-functionally with product management, engineering, design, legal, research, and operations teams to build impactful safety features, models, and systems. This high-impact role requires deep customer empathy, insatiable curiosity to uncover platform risks; and competencies to explore large datasets, develop statistical models, and design data-driven strategies for products that provide safe and engaging experiences for customers.

You’ll report to the Director of Data Science for the SCC org.

Responsibilities:

• Leverage data and analytical frameworks to identify opportunities for improving community trust and safety
• Partner with product managers, engineers, designers, marketers, and operators to translate insights into scalable, safety-forward decisions
• Design and analyze online experiments; interpret and communicate results to influence product launch decisions
• Build and monitor key metrics that reflect rider and driver safety, product health, and policy compliance
• Develop rigorous measurement strategies to evaluate the effectiveness of safety features, interventions, and detection systems
• Drive proactive risk identification and continuous improvement through analysis, experimentation, and iteration
• Mentored junior data scientists by providing guidance, feedback, and support to accelerate their technical and soft skill growth and impact.

Experience:

• Degree in a quantitative field such as Statistics, Economics, Applied Mathematics, Operations Research, or Engineering (advanced degrees preferred), or equivalent professional experience
• 3+ years of industry experience in data science or product analytics roles
• Proficiency in SQL with ability to write efficient queries on large, complex datasets
• Experience programming in Python or R, especially for data analysis, visualization, and modeling
• Strong foundation in statistical analysis and experimentation, including A/B testing design and/or Causal Inference techniques
• Excellent written and verbal communication skills with ability to influence cross-functional partners and executives, and translate data into compelling stories
• Self-starter with a curious mindset and a strong sense of ownership
• Ability to combine business intuition with the application of advanced solutions
• A passion for keeping up with the latest ongoings in Data Science and Machine Learning communities, and an obsession for data quality
• Prior experience in Trust & Safety, or Platform Integrity domains is a plus

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 at least 3 days per week, including 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 Toronto area is CAD $108000-$135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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

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

The Verticals team encompasses 3 critical and unique products / marketplaces within Lyft: airports, scheduled rides, and events. Airports are one of the most important, impactful, and complex parts of Lyft’s Rideshare business, as they are a key part of both the rider and driver Lyft experiences and have unique considerations and dynamics. Scheduled rides allow riders to book a ride in advance with high reliability, and enable drivers to add structure to their work schedule. Lastly, events such as concerts or sporting games require similar considerations of special operations to ensure a seamless experience for both riders and drivers. 

As a Data Scientist on the Verticals team, you will collaborate with engineering, product, design, and operations to think critically about the current rider and driver experience and implement product enhancements to facilitate market growth. The ideal candidate can apply strong business acumen to propose product changes, develop end-to-end technical solutions, and is comfortable working with a highly cross functional team. In this role, you will help us tackle problems such as:

• How can we efficiently match riders and drivers together in these unique marketplaces, to minimize ETAs and improve the driver experience? 
• Are we able to forecast ride demand and implement driver guidance to ensure riders can rely on Lyft for an event ride?
• What is the most helpful way to display ride information to drivers so they can make informed decisions?
• What rider segments should we target with ride incentives to grow our marketshare for these verticals? 

Responsibilities:

• Construct and fit statistical or optimization models to make production decisions such as changes to how we match riders and drivers; focusing on model proposal and offline model development 
• Leverage data and analytic frameworks to identify opportunities for growth and efficiency, recommending technical solutions to drive business impact 
• Design and analyze online experiments, including communicating results, acting on launch decisions, and recommending next steps based on learnings
• Partner with product managers, engineers, marketers, designers, and operators to translate data insights into decisions and action
• Develop analytical frameworks to monitor business and product performance, leveraging experiments and causal inference
• Establish metrics that measure the health of our products, the business, as well as the driver experience

Experience 

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

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 at least 3 days per week, including 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 Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

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.

Lyft’s Data Science Team builds mathematical models underpinning the platform’s core services. Compared to other technology companies of a similar size, the set of problems that we tackle is incredibly diverse. They cut across optimization, prediction, modeling, inference, transportation, and mapping. We are hiring motivated experts in each of these fields. We're looking for someone who is passionate about solving mathematical problems with data, and are excited about working in a fast-paced, innovative and collegial environment.

You will report into a Science Manager.

Responsibilities:

• 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 run both simulated and live traffic experiments
• Analyze experimental and observational data; communicate findings; facilitate launch decisions

Experience:

• Ph.D. in Statistics, Operations Research, Mathematics, Computer Science, or other quantitative fields
• 2+ years professional experience in a technology companies
• Passion for solving unstructured and non-standard mathematical problems
• End-to-end experience with data, including querying, aggregation, analysis, and visualization
• Proficiency with Python, or another interpreted programming language like R or Matlab
• Willingness to collaborate and communicate with others to solve a problem

Benefits:

• Extended health and dental coverage options, along with life insurance and disability benefits
• Mental health benefits
• Family building benefits
• Child care and pet benefits
• Access to a Lyft funded Health Care Savings Account
• RRSP plan with company match to help save for your future
• In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service 
• Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
• Subsidized commuter benefits and Lyft ride credits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind.  Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

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 at least 3 days per week, including 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 Toronto area is CAD $108,000 - CAD $135,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

Lyft may use artificial intelligence to screen applicants, however, Lyft employees make the ultimate selection and hiring decisions.

This job fills an existing vacancy.

Understanding and improving how we deliver and optimize ads to Pinners is fundamental to Pinterest’s long-term success.  We’re looking for a data scientist to join our team in pushing the boundaries in ads delivery and optimization. You will be a key member of an organization of talented data scientists innovating on ads delivery.

What you’ll do:

We are looking for an experienced and highly capable Data Scientist to help us drive step function improvements in our ads delivery at Pinterest. In this role, you will:

• Strategy: Evolve our strategy by working closely with product and engineering leaders to build on past learnings and shape our platform's future.
• Experimentation: Improve our experimentation capabilities and tools for assessing our ad delivery system, advise on best practices, identify flaws, and build tools and frameworks for experiment analysis.
• Leadership: Lead and mentor peers, improving team output through continuous, candid feedback that recognizes strengths and identifies areas for growth. Be a technical leader for junior data scientists based in the Toronto office.
• Communication: Clearly and concisely communicate complex analytical findings and insights to stakeholders with varying technical backgrounds.
• Continuous Learning: Stay informed on the latest developments in data science, causal inference, and advertising technology to drive innovation.
• Leverage AI to seek faster execution (i.e. draft, prototype, outline) and explore alternative options (i.e. iterate, compare approaches)
• Leverage AI to synthesize information (summarize, distill themes) and automate repeatable tasks (documentation, reporting, QA checks)

What we’re looking for:

• 8+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems on web-scale data, preferred to have working knowledge of ads delivery and optimization systems.
• Proven ability to apply scientific methods to solve real-world problems on web-scale data
• Expertise in SQL and Python
• Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions
• Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership and product teams 
• Experience leading key technical projects and substantially influencing the scope and output of others
• Experience in digital ad delivery stacks preferred
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
• High integrity and ownership: you protect sensitive data, avoid over-reliance on AI, and remain accountable for final decisions and deliverables.
• Bachelor’s or Master’s degree in a relevant field such as Data Science, or equivalent experience

This job posting is for an open vacancy. Please note that the company utilizes artificial intelligence to screen applicants for the positions.

Relocation Statement:

• This position is not eligible for relocation.

In-Office Requirement Statement:

• We let the type of work you do guide the collaboration style. That means we're not always working in an office, but we continue to gather for key moments of collaboration and connection.
• This role will need to be in the office for in-person collaboration 1-2 times per half and therefore can be situated anywhere in Ontario. 

#LI-CH1 #LI-HYBRID

Upwork Inc.’s (Nasdaq: UPWK) family of companies connects businesses with global, AI-enabled talent across every contingent work type including freelance, fractional, and payrolled. This portfolio includes the Upwork Marketplace, which connects businesses with on-demand access to highly skilled talent across the globe, and Lifted, which provides a purpose-built solution for enterprise organizations to source, contract, manage, and pay talent across the full spectrum of contingent work. From Fortune 100 enterprises to entrepreneurs, businesses rely on Upwork Inc. to find and hire expert talent, leverage AI-powered work solutions, and drive business transformation. With access to professionals spanning more than 10,000 skills across AI & machine learning, software development, sales & marketing, customer support, finance & accounting, and more, the Upwork family of companies enables businesses of all sizes to scale, innovate, and transform their workforces for the age of AI and beyond.

Since its founding, Upwork Inc. has facilitated more than $30 billion in total transactions and services as it fulfills its purpose to create opportunity in every era of work. Learn more about the Upwork Marketplace at Upwork.com and follow us on LinkedIn, Facebook, Instagram, TikTok, and X; and learn more about Lifted at Go-Lifted and follow on LinkedIn.

Sr. Lead AI Research Scientist, AI Evaluation and Reliability

The AI Foundations team leads core research and development across the training, evaluation, and deployment of AI systems that power Uma, Upwork’s flagship AI model, and other customer-facing generative AI capabilities. As a Sr. Lead AI Research Scientist focused on AI Evaluation and Reliability, you will drive high-impact research initiatives that improve the trustworthiness, robustness, and real-world performance of AI systems operating at marketplace scale.

At the Sr. Lead level, this role combines deep technical expertise with cross-functional leadership. You will identify and lead research efforts that address systemic reliability challenges, partner closely with engineering and product teams to translate research into production outcomes, and help shape how Upwork evaluates AI performance in real work scenarios. Your work will support AI systems embedded in retrieval-based workflows, agentic architectures, and human plus AI collaboration patterns, while contributing to Upwork’s broader AI research strategy and external presence.

Responsibilities:

• Lead applied research initiatives focused on AI evaluation, reliability, and robustness, defining success metrics tied to customer impact and production readiness.

• Design and validate methods to measure and mitigate AI reliability risks, including uncertainty estimation, hallucination detection, and identification of model failure modes.

• Partner cross-functionally with engineering, data science, and product teams to integrate research outcomes into customer-facing AI systems and workflows.

• Own research projects end to end, from problem framing and hypothesis development through experimentation, prototyping, and synthesis of results.

• Influence technical direction across teams by surfacing insights, proposing scalable solutions, and aligning stakeholders on priorities and tradeoffs.

• Mentor researchers and engineers through technical guidance, feedback, and collaborative leadership on shared initiatives.

• Contribute to Upwork’s external research footprint through publications, presentations, and engagement with the broader AI research community.

What it takes to catch our eye:

• Proven experience leading applied AI research that balances scientific rigor with real-world deployment constraints and business impact.

• A strong record of research contribution through publications, internal innovation, or demonstrable influence on production AI systems.

• Deep proficiency with Python and modern deep learning frameworks such as PyTorch, with hands-on experience evaluating and improving large-scale models.

• An adaptive approach to integrating AI tools into research and development workflows to accelerate experimentation, improve evaluation quality, and share best practices with others.

• A collaborative, growth-oriented mindset with the ability to mentor peers, communicate complex ideas clearly, and thrive in a fast-evolving, bottom-up environment.
  
  

Come change how the world works.

Upwork is establishing an operational hub in Toronto, Canada. The new office is expected to be fully operational by Q4 2026. This role will require 3 days in office once we have an office open.

This position will initially be employed through a partner to ensure a seamless hiring process while we establish the hub. Once the hub is established, there may be opportunities to transition to employment with Upwork, depending on business needs and other requirements. While employed by the partner, you’ll work as part of Upwork’s team, with access to our resources, culture, and growth opportunities.

Our partner will offer competitive benefits. When Upwork’s hub is established, we will be excited to offer employment and benefits directly as business needs require. 

Upwork is committed to building a diverse, inclusive, and equitable workforce. Employment decisions are made without regard to race, color, religion, gender, sexual orientation, gender identity, national origin, disability, or any other status protected by applicable law.

We use BrightHire, an AI-enabled tool, to record interviews and summarize interview transcripts. The tool allows the interviewer to focus on the discussion and does not score or evaluate candidates or make recommendations. The interview transcripts are reviewed, and decisions are only made by humans. Candidates who prefer not to have their interview recorded through BrightHire can opt out when the interview is scheduled.

To learn more about how Upwork processes and protects your personal information as part of the application process, please review our Global Job Applicant Privacy Notice and the Applicant Privacy Addendum (Canada).

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist Intern who can help us discover the value out of our rich and large datasets. Our ideal team member will have the mathematical and statistical expertise you’d expect, but a natural curiosity and creative mind that’s not so easy to find. As you mine, interpret and clean our data, we will rely on you to ask questions, connect the dots, and uncover opportunities that lie hidden within—all with the ultimate goal of realizing the data’s full potential. You will join a team of data specialists, but will “slice and dice” data using your own methods, creating new visions for the future. If you love technology and are keen to join an industry leader — we would love to hear from you!

What you'll do:

As a Data Scientist Intern, you will be a crucial part of producing innovative analytics from Geotab’s big data environment. We believe that there is collective value in the massive amount of data arising from all of our sensors across the globe. And most importantly, we believe this data can be used to improve safety, infrastructure, and productivity for our customers. You will work with our team of data scientists and engineers who have curated our data repository and have created a series of near real-time and historical datasets. You will leverage data mining techniques, Machine Learning, Deep Learning, Neural Networks and other Artificial Intelligence and statistical analysis tools to build models and high-quality prediction systems to help our customers make informed and smarter decisions. You will work closely with Data Analysts, Data Engineers, Professional Services, Data Privacy & Governance, firmware as well as other internal departments such as Software Development and Solutions Engineering to achieve these objectives.

The opportunity:

• 8+ month work-term beginning September 2026.
• Full-time, paid internship: Monday - Friday, 37.5hrs/week.
• Your first week at Geotab begins with 'GEO Launch' - a one-week Employee Orientation. Click here to learn more!
• Learn more about the Geotab Campus Program here.
• This posting is for an existing vacancy.

How you'll make an impact:

• The primary objective of this internship is to develop a "Reasoning & Automation" solution that evolves Geotab Ace into a fully integrated, context-aware assistant. Key goals include:
  • Multi-Modal Ingestion: Implement a multi-modal ingestion layer (leveraging technologies like Google's LiveAPI) capable of processing screen content, audio, and text simultaneously to establish real-time user context.
  • Contextual Enrichment: Develop mechanisms to automatically enrich user prompts with environmental state (e.g., current page URL, visible data charts), eliminating the need for users to manually explain their context.
  • Proactive Assistance & Navigation: Extend the reasoning capabilities of the agent to not only answer data queries but also guide users through complex workflows ("Where do I go to...") and offer proactive support.
  • Optimization of RAG & SQL Generation: Continue to refine the underlying RAG architecture and "text-to-SQL" generation for Google BigQuery to ensure the answers provided are accurate, safe, and efficient.

What you'll bring to the role:

We are a Canadian leader in digital automotive solutions. Our flagship brands — AutoTrader.ca, AutoSync, Dealertrack Canada and CMS — help Canadians buy, sell, and finance vehicles with confidence. 

AutoTrader.ca is Canada’s largest automotive marketplace, with over 25 million monthly visits. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond.

What's in it for you:

We understand that there is life at work and life outside of work. Here are a few benefits we all benefit from that support us to be our creative best. 

• Gym discounts 

• Employee and Family Assistance program 

• Virtual wellness events 

• Conferences & training budget 

• Regular internal training programs 

• Financial planning with 3% matching Pension  

• Competitive salary 
• Annual bonus structure 

For a career where you can drive our business and shape your future, apply now. 

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist Intern within the Insights & Integrations Consultancy team that will support ongoing projects by assisting in data analysis, visualization, and the development of solutions that help optimize fleet operations and enhance customer decision-making. If you love technology and are keen to join an industry leader — we would love to hear from you!

What you'll do:

As a Data Scientist Intern within the Insights & Integrations Consultancy team, you will gain hands-on experience in leveraging data to drive strategic insights for customers and partners. In this role, you will have the opportunity to work with Geotab’s open data platform, learning how to explore and interpret telematics data to solve real-world business challenges. You will collaborate with cross-functional teams, including Data Scientists, Product Managers, and Integration Engineers, to support key initiatives focused on portfolio expansion, retention, and solution innovation.

Throughout your internship, you will develop a deeper understanding of industry trends, fleet analytics, and Geotab’s ecosystem, while contributing to meaningful projects that have a direct impact on customers and partners.

The opportunity:

• 12 month work-term beginning September 2026.
• Full-time, paid internship: Monday - Friday, 37.5hrs/week.
• Your first week at Geotab begins with 'GEO Launch' - a one-week Employee Orientation. Click here to learn more!
• Learn more about the Geotab Campus Program here.
• This posting is for an existing vacancy.

How you'll make an impact:

• Develop foundational knowledge of the Geotab ecosystem and telematics data, assisting in data exploration, visualization, and analysis to support customer and partner insights.
• Collaborate with Data Scientists and cross-functional teams to optimize the use of Geotab’s technology, providing analytical support for ongoing projects.
• Assist in building and refining data-driven dashboards for internal and external stakeholders, facilitating informed decision-making.
• Support continuous improvement initiatives by gathering feedback, identifying trends, and contributing to data-driven recommendations.
• Work closely with mentors to apply statistical and machine learning techniques in fleet analytics, helping develop predictive models and insights under guidance.
• Contribute to proof-of-concept development, assisting in the creation of small-scale models or prototypes that demonstrate the feasibility and impact of analytics-driven solutions.
• Stay informed on industry trends, emerging data science techniques, and best practices to enhance analytical capabilities.
• Maintain and update documentation on data analysis processes, methodologies, and findings for internal knowledge-sharing.
• Assist in maintaining data pipelines using SQL and Python-based workflows to support ongoing analytics initiatives.

What you'll bring to the role:

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

** This role is not eligible for hire in the United States - we are hiring only in Toronto, Ontario, Canada for summer 2026.

About Clutch:

Clutch is Canada’s largest online used car retailer, delivering a seamless, hassle-free car-buying experience to drivers everywhere. Customers can browse hundreds of cars from the comfort of their home, get the right one delivered to their door, and enjoy peace of mind with our 10-Day Money-Back Guarantee… and that’s just the beginning.

Named one of Canada’s top growing Companies two years in a row and also awarded a spot on LinkedIn’s Top Canadian Startups list, we’re looking to add curious, hard-working, and driven individuals to our growing team.

Headquartered in Toronto, Clutch was founded in 2017. Clutch is backed by a number of world-class investors, including Canaan, BrandProject, Real Ventures, D1 Capital, and Upper90. To learn more, visit clutch.ca.

About the role:

Clutch is hiring a Staff Data Scientist to lead major improvements to our pricing algorithms and applied machine learning systems.

This is a high-ownership role for someone who thrives in ambiguity, can go deep on research and modeling, and has a track record of deploying ML to production with measurable business impact. You’ll work on ML systems that already drive real outcomes - including pricing models that purchase >$1M of vehicles per day with no human intervention - with significant opportunity to take them to the next level as we scale.

You’ll join a small, high-leverage data team where your work will be visible, measurable, and business-critical, with the chance to expand into additional high-impact ML domains like lending, logistics optimization, fraud detection, and recommendations. In this role, you’ll own problem areas end-to-end from identifying opportunities and shaping the approach, to shipping production models and driving measurable improvements in margin and conversion.

What you'll do:

• Own and drive improvements to Clutch’s pricing algorithms, balancing margin, conversion, and customer experience.
• Deep-dive into market and vehicle data to identify the key relationships between vehicle attributes, market dynamics, and pricing outcomes.
• Build, validate, and deploy ML models and algorithms into production — and iterate quickly based on real-world performance.
• Lead feature engineering, model evaluation, and experimentation design.
• Partner with Product, Engineering, Strategy & Ops, Sell-To-Clutch & Retail to prioritize the highest-impact opportunities.
• Contribute to additional applied ML domains as needed, including:
• Financing / lending decisioning
• Fraud detection
• Search and discovery optimization
• Vehicle recommendations / personalization

What we’re looking for:

• 8+ Years of Experience: A proven track record as a Data Scientist, with a history of delivering measurable business impact through machine learning.
• 0-to-1 Strategic Autonomy: Proven ability to navigate high-ambiguity environments. You own the roadmap by evaluating the data, identifying untapped opportunities, and formulating your own research theories.
• End-to-End Technical Ownership: Deep Python proficiency with the ability to own the entire lifecycle: from raw data exploration and feature engineering to model architecture and production deployment.
• Production-Grade ML: Strong experience building and deploying traditional ML algorithms into live environments, ensuring they are robust, scalable, and maintainable.
• Foundational Rigor: Strong statistical fundamentals and a disciplined approach to validation. You ensure that every model is built on a foundation of sound logic and clean data, maintaining high standards for accuracy and reliability without external oversight.
• Excellent Communication: Able to bridge the gap between complex technical findings and business ROI. You can distill "black box" complexity into clear trade-offs and actionable recommendations for business leaders.

What You'll Be Doing:

• Work directly on building, deploying, and iterating on machine learning models and agentic workflow features that address real customer needs
• Apply ML techniques to improve accuracy and overall system performance, ensuring solutions are robust, reliable, and production-ready for customers
• Improve, implement, and validate ML models and agentic workflows supporting submission intake, underwriting decision-making, and automation tasks
• Deploy and adapt autonomous agent behaviors into customer-specific workflows, translating core AI capabilities into practical solutions
• Develop and maintain evaluation pipelines, monitoring systems, and performance metrics to ensure reliability under evolving production conditions
• Monitor production systems via logs, metrics, and user feedback to diagnose issues, debug failures, and drive resolution
• Take end-to-end ownership of problems — implementing fixes or coordinating with engineering and infrastructure teams as needed
• Partner closely with Data Science and Engineering teams to iterate quickly and deliver high-impact solutions

Who We Hope You Are:

• Bachelor's or master’s degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or a related field with foundational knowledge in machine learning, deep learning, and natural language processing.
• Experience working in a fast-paced, cross-functional environment
• 2+ years of experience as a Machine Learning Engineer, Applied Scientist, or similar role delivering ML solutions in production
• Experience working directly with customers or stakeholders to translate business needs into technical solutions
• Hands-on experience adapting, extending, and deploying ML/LLM systems (including agentic workflows and prompt engineering) in real-world use cases
• Strong experience with experimentation, evaluation, and monitoring pipelines, including analyzing production logs and debugging systems
• Experience deploying and iterating on ML systems in cloud environments in collaboration with engineering teams
• Proven track record of ownership — driving issues through to resolution in production systems

Base Salary Range: $155,000 - $180,000
Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package also includes bonus, stock options, benefits and additional perks. 

MaintainX is the world's leading AI-powered maintenance and asset management platform, serving 13,000+ customers including Duracell, Shell, Cintas, and Brenntag. We raised $150M in Series D funding led by Bessemer Venture Partners and Bain Capital Ventures, bringing our total funding to $254M. We were named to the Forbes 2025 Cloud 100, the definitive ranking of the top 100 private cloud companies in the world. We're growing fast and hiring the engineering talent to match.

We're looking for a Senior Software Engineer to own the constraint-solving engine behind our Scheduling Agent, one of the most strategic bets on our Planning & Scheduling roadmap. The engine is a Python service built on CP-SAT that takes work orders, technicians, and a mix of hard and soft constraints, and produces a feasible weekly schedule that enterprise maintenance teams can trust. Your focus will be evolving the solver to handle increasingly complex, real-world scheduling scenarios and exposing it as tools for GenAI agent workflows.

This is a high-ownership role. You'll have the space to shape the modeling approach, partner closely with product and design on what scheduler users actually need, and ship iteratively against feedback from real enterprise customers.

What you'll do

• Own and evolve the Python optimization service that powers the Scheduling Agent, modeling, solving, and iterating on the constraint formulation as new use cases emerge.
• Design and implement increasingly sophisticated scheduling capabilities: trade and crew constraints, irregular capacity patterns, production downtime windows, multi-site considerations, and reactive re-scheduling.
• Build and maintain API routes and tools that expose the solver to GenAI agent workflows (tool calling, structured input/output).
• Partner with PM and design to translate messy real-world scheduling problems into solver constraints, and push back when "optimal" isn't what users actually want.
• Iterate the solver with real users via design partnerships and pilot deployments. Take feedback from human schedulers seriously and reflect it back into the model.
• Contribute to the surrounding Python service: performance, observability, testing, and reliability of the optimization runtime.
• Help shape how scheduling intelligence integrates with the broader MaintainX product over time, including learning from execution data to improve solver inputs.

About you

• 5+ years of professional software engineering experience, with significant time spent on optimization, constraint programming, or operations research problems shipped to real users.
• Strong fluency with CP-SAT and at least one other optimization paradigm (MILP via Gurobi/CPLEX/HiGHS, metaheuristics, or similar). You've hit the limits of one approach and made informed choices about when to use which.
• Solid Python service engineering: APIs, async, testing, profiling, observability. You can own a production service end-to-end.
• Academic grounding in Operations Research, Industrial Engineering, Computer Science, or a related quantitative field, at minimum a strong undergraduate foundation; advanced degrees are common in this space but not required.
• Track record of iterating optimization systems with real users, you've felt what happens when a human rejects the "optimal" answer and you've redesigned the model in response.
• Product mindset and delivery orientation, you ship, you measure, you iterate. You think about the user outcome, not just the objective function.
• Comfort with ambiguity. You can co-design the constraint data model with the team rather than waiting for a clean spec.
• Familiarity with GenAI tooling (LLM tool calling, structured output, prompt design for constrained generation) is expected.

Nice to have

• Experience at a known, reputable product company shipping optimization or scheduling products at scale.
• Exposure to learning-augmented optimization, using historical execution data to estimate durations, priors, or constraint weights.
• Domain experience in scheduling, workforce management, field service, manufacturing, logistics, or similar resource-constrained planning problems.
• Tech-lead experience or interest in growing into a tech-lead role on this team.

What's in it for you

• Competitive salary and meaningful equity opportunities.
• Healthcare, dental, and vision coverage.
• 401(k) / RRSP enrollment program.
• Take what you need PTO.
• A Work Culture where:
• You'll work alongside folks across the globe that reflect the MaintainX values: Smart Humble Optimists.
• We believe in meritocracy, where ideas and effort are publicly celebrated.

About us

Our mission is to deliver one platform for maintenance, repair & operations teams to keep the physical world running. We believe the greatest asset in any organization is the people. That's why we built an intuitive, mobile-first solution to help boost productivity and collaboration across teams and locations.

MaintainX is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

#LI-Remote

As a Senior ML Scientist at Ada, you will own the quality and reliability of the AI features that power our AI Agent platform for customer support. You will partner with Product Managers, Engineers, and Designers to frame problems, design experiments, and make evidence-based decisions that improve outcomes for customers and end users. You will primarily deliver simple and highly reusable evaluation and analysis code, and you will collaborate with engineers to productionize changes. To be successful, you will develop a deep understanding of Ada’s product and empathize with our users to find the best ways to solve customer problems. If you’re excited to shape the future of AI-driven customer support, we would love to hear from you.

About You

• 5+ years of industry experience as a Data Scientist, Machine Learning Engineer, or similar with shipped work that moved product metrics
• Deep experience applying large language models to customer problems
• Excellent communicator, able to explain experimental results and complex ML concepts to diverse audiences
• You design reliable experiments and datasets that translate to production impact
• Strong software skills in Python, writing clean, production-ready code and documents
   

Outcomes

• Run rapid, reliable experiments with sound statistical methods, reproducible pipelines, and clear readouts that drive product decisions
• Lead design choices across model selection, retrieval and grounding, prompting, and tool use, framing tradeoffs in quality, safety, cost, and latency
• Reduce critical AI failure modes, for example hallucinations and prompt injection, through targeted testing and red teaming
• Partner with PM, Engineering, and Design to prioritize customer use cases and failure modes, turning insights into changes that improve automated resolutions, CSAT, cost per conversation, and latency
• Coach and mentor peers in the Product Development org in AI feature design, experimentation, and measurement. Provide crisp and actionable feedback to help raise the standard for AI feature quality

Our co-op/intern experience is unique and designed to prepare you for professional success. Our ultimate goal is to give you the mentorship, training and work experience you need to start your career successfully!

As part of Visiers R&D organization, our data science team is responsible for the development of advanced numerical algorithms and statistical techniques that generate business insights from human resource data. Mentored by an experienced Data Scientist you will collaborate on projects that match both your interests and Visier business needs. This could be software engineering focused (e.g. enhancing our machine learning pipelines or prototyping of automated insight generation), or research focused (e.g. unveiling compelling insights into the workforce from our unique multi-million employee cross-customers data set).

What you'll be doing...

• Modelling the problem at hand, such that it directly solves underlying business problems
• Brainstorming to identify the correct data required to solve business problems
• Performing statistical analysis on data to build statistical/machine learning models
• Identifying the right metrics to measure the success of the models and projects
• Communicating and presenting your work to stakeholders across the organisation
• Conducting independently research, in order to gain domain knowledge and learn cutting-edge techniques

What you'll bring to the table...

• Strong understanding of statistics and how to apply scientific methods to data using algorithms
• Coding skills in Scala, Python or other relevant languages
• Attention to detail and big picture thinking
• Currently pursuing your Masters or PhD
• Knowledge in one of the following areas would be an advantage:
• Hypothesis testing
• Machine learning techniques
• Scientific analysis and knowledge generation

The base pay range for this position in Canada is $5,500k / month.

The compensation offered will be determined by factors such as relevant qualifications, experience, knowledge and skills. Many of our positions are eligible for additional types of compensation (e.g., commission plans, bonus, etc.) which our Talent Acquisition team will share with you if you interview for the role.

About Inspiren 

Inspiren offers the most complete and connected ecosystem in senior living. Founded by Michael Wang, a former Green Beret turned cardiothoracic nurse, Inspiren proves that compassionate care and technology can coexist - bringing peace of mind to residents, families, and staff.

Our integrated solutions seamlessly fit into existing workflows, capturing everything happening within a community. Backed by nurse specialists and powerful analytics, we provide the data operators need to make informed clinical and operational decisions - driving efficiency, profitability, and better care outcomes.

About the Role

We're looking for a Senior Data Scientist to bring rigor, modeling depth, and a bias toward automation to the data that powers Inspiren. You'll work across the organization, including with our Computer Vision, Machine Learning Engineering, Hardware, and Embedded Systems teams, building models, designing statistical evaluations, and turning one-off analyses into durable workflows that keep improving the product. You should be deeply familiar with the end-to-end ML lifecycle, comfortable reasoning about both classical statistics and modern ML systems, and energized by the opportunity to weave AI into data science workflows.

What you'll do

• Build models and statistical analyses that surface insights about outcomes and performance across Inspiren’s systems
• Design and run rigorous evaluations: offline and online experiments (A/B, shadow deploys, etc.) for new models and product changes
• Identify, evaluate, and integrate new datasets that expand what we can learn and measure
• Lead root-cause investigations when models or systems underperform in the field, and turn findings into concrete recommendations for improvement
• Incorporate AI into data science workflows, using LLMs and agentic tooling to accelerate analysis, code generation, documentation, and decision-making, and help shape how the team adopts these practices
• Reason how to incorporate multiple modalities and sensor data into algorithmic development and performance measurement

About you

• 5+ years of experience in data science, with a focus on statistical modeling and ML systems
• Strong modeling and statistical foundations. You're comfortable choosing the right tool for the problem, whether simple heuristics through ML
• Experience partnering with ML engineering teams, including familiarity with how production ML systems are evaluated and monitored
• Fluency with a modern data science stack: Python, Pandas, PyTorch, Databricks, MLflow, or similar tools for working with data and ML at scale
• Hands-on experience using AI tools (LLMs, coding copilots, agentic workflows) to speed up your own work, and curiosity to experiment with AI tools
• Strong data instincts and a pragmatic bias toward solutions that work in messy, real-world conditions
• A collaborative mindset and interest in working with a diverse teams
• Able to scope, prioritize, and deliver work independently
• Excited about working at an early-stage startup where your work directly shapes care outcomes

Bonus skills

• Experience working on spatiotemporal problems (sensor data, trajectories, event streams, or similar)
• Experience working with health or clinical data
• Healthcare or senior living domain experience

Details

• The annual salary for this role is $170,000-$200,000 + equity + benefits (including medical, dental, and vision) 
• Flexible PTO
• Location: Remote, US or Canada. NYC preferred.
• Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.

Who you are:

We are always looking for amazing talent who can contribute to our growth and deliver results! Geotab is seeking a Data Scientist who will assist in the design and construction of Geotab's data mining and model building processes from vast amounts of raw data. This position collaborates with internal technical teams in analyzing trends to make improved decision-making in producing effective customer-facing products. If you love technology, and are keen to join an industry leader — we would love to hear from you! 

What you'll do:

As a Data Scientist, your key area of responsibility will be designing and constructing Geotab’s data modeling processes, creating algorithms and predictive models to solve complex business problems, and generating queries from Big Data Infrastructure. You will also be responsible for developing Machine Learning models, testing product performance, and maintaining reports and dashboards to drive key business decisions. You will need to work closely with Geotab’s internal technical teams to gather requirements and ensure data-driven products meet expectations.

To be successful in this role you will be a strong team-player with an entrepreneurial mindset who is comfortable in a flat organization and able to engage with all levels of the organization. In addition, the successful candidate will have strong analytical and problem-solving skills with high accuracy and meticulous attention to detail. The successful candidate will also be highly organized and able to manage multiple tasks and projects simultaneously to ensure timely results.

How you'll make an impact:

• Design and construct Geotab’s data modeling processes. 

• Create algorithms and predictive models to extract information required to solve complex business problems. 

• Generate queries from Geotab’s Big Data Infrastructure from Data Warehousing database (i.e. Google BigQuery). 

• Use Machine Learning (ML) packages (e.g. Scikit-learn and Tensorflow) to develop ML models and features. 

• Test the performance of data-driven products and make recommendations for improving Geotab’s product suite. 

• Collaborate with internal technical teams to gather requirements. 

• Responsible for the design, development, and maintenance of ongoing metrics, reports, analyses, and dashboards to drive key business decisions. 

• Support a platform providing ad-hoc and automated access to large dataset.

What you'll bring to the role:

Why job seekers choose Geotab:

Why job seekers choose Geotab:

What You Will Do:

• Conduct original research and develop deep distributed reinforcement learning (RL) training systems tailored for the complex gameplay features of Varsapura.
   
   
• Collaborate with cross-functional teams to understand the requirements of gameplay features and ensure machine learning algorithms are effectively integrated into the design.
   
• Take ownership of research project roadmaps, collaborating with engineers to iterate on feature requirements and managing risk for production deployment and maintenance.
   
• Explore and implement advanced techniques in asset processing to ensure high-quality and optimized assets for the game development cycle.
   
• Stay up to date with the latest advancements in machine learning, computer vision, and data compression, applying these technologies to improve the overall gaming experience.

What We Are Looking For:

• MS or PhD degree in Computer Science, Statistics, or a related field, or 8+ years of equivalent high-level research experience.
   
• Strong background in applied machine learning with an expertise on reinforcement learning algorithms 
   
• Hands-on experience designing and developing reinforcement learning tasks from end to end; project experience involving 3D environments, complex action space and spatial reasoning is a strong plus.
   
• Proficiency in programming languages such as Python and C++, and expertise with deep learning frameworks such as PyTorch or TensorFlow.
   
• Experience working in game development with a strong understanding of gameplay systems, and real-time constraints.
   
• Familiarity with distributed training on cloud platforms such as AWS or GCP, including experience debugging performance and managing large-scale experiments.
   
• Solid knowledge of asset processing pipelines, including 3D modeling, texturing, and animation.
   
• Strong problem-solving skills and the ability to work effectively in a collaborative team environment.
   
• Record of publications or contributions to the machine learning and computer vision communities.

Benefits:

The base pay range for this position is $180,000 to $300,000 USD per year. Actual pay is based on location and may vary depending on relevant knowledge, skills, and experience from the candidate. Total compensation may include salary, company bonuses, sign-on bonuses, relocation package, and other benefits such as:

• 100% employer-paid healthcare premiums for you and your dependents
• Generous paid time off
• 401K / RRSP plan
• Employer-paid life and disability insurance
• Team-building activities throughout the year
• Flexible working hours

About the team + role

We are building an elite team, applying frontier technologies to the world’s biggest financial problems. We’re looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn’t a place for complacency, it’s where ambitious people do the best work of their careers. We’re a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards. 

The Brokerage Data Science team uses data to inform automated modeling decisions and generate insights that guide product and business strategy. The team works closely with product, engineering, and operations partners to improve how customers engage with Robinhood’s platform. You’ll contribute to shaping personalized product experiences that support customers throughout their investing journey!

As a Senior Data Scientist, ML, you will lead the development of recommendation systems for prediction markets, one of Robinhood’s fastest-growing areas. You will work closely with product managers and engineers to identify opportunities for personalization, design modeling approaches, and implement solutions that improve customer engagement. This role starts with building personalization for prediction markets and will expand to additional product surfaces as the strategy evolves.

This role is based in our Menlo Park, CA and New York, NY office(s), with in-person attendance expected at least 3 days per week.

At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams. 

What you’ll do

• Build and improve recommendation system algorithms to personalize customer experiences across prediction markets and other product surfaces
• Partner with product managers to identify areas for personalization and define measurable success criteria
• Develop features and models that improve relevance and user interaction with our prediction markets offerings
• Collaborate with software and machine learning engineers to design and implement scalable feature pipelines and the ranking systems
• Design and run experiments to evaluate model performance and measure incremental impact on customer engagement

What you bring

• You have 5+ years of experience building recommendation systems in customer-facing products (e.g., streaming, marketplace, or on-demand platforms)
• You are proficient in Python and SQL and have strong experience with machine learning systems and production modeling
• You have experience with experimentation methods and causal inference to evaluate model performance
• You communicate clearly and collaborate effectively with product, engineering, and data science partners
• You demonstrate ownership by driving projects from concept through implementation

What we offer

• Challenging, high-impact work to grow your career.
• Performance-driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching.
• Best-in-class benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents.
• Lifestyle wallet — a highly flexible benefits spending account for wellness, learning, and more.
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits.
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.

We are TRADER, a Canadian leader in digital automotive solutions. Our flagship brands - AutoTrader.ca, AutoSync, Dealertrack Canada and CMS - help Canadians buy, sell, and finance vehicles with confidence. 

Learn more at tradercorporation.com. 

As part of AutoScout24 group, Europe’s largest online car marketplace, we’re shaping the future of automotive retail in Canada and beyond. 

As Senior Data Scientist, you will be key contributor within our global Data Science organization, shaping AI and machine learning systems that sit at the core of our marketplace platforms across Europe and Canada. 

You design, build, and operate machine learning and GenAI systems that run in production and matter to the business. You work on complex, ambiguous problems, exercise strong technical judgment, and take responsibility for outcomes - not just models. While this is a hands-on role, you are also expected to influence technical direction, raise the bar for engineering practices, and enable other data scientists and engineers to succeed. This position is permanent and based in Toronto. 

What you’ll do 

• Own ML and GenAI systems end-to-end in production, including problem framing, system design, deployment, monitoring, and continuous improvement 

• Make sound architectural and methodological decisions for ML systems on AWS, balancing robustness, observability, cost, and long-term maintainability 

• Partner closely with Product, Engineering, and Business leaders to turn ambiguous problems into ML-enabled product solutions with clear outcomes 

• Operate and evolve ML systems deployed across multiple countries and markets, accounting for differences in data distributions, regulations, and constraints 

• Mentor other data scientists through hands-on technical guidance, design reviews, and shared ownership of systems 

What you’ll need  

• Advanced degree in Computer Science, Engineering, Mathematics, or a comparable field 

• 5+ years of experience building and owning production ML systems end-to-end in a real-world environment 

• Strong hands-on expertise in Python and modern ML frameworks, with the ability to ship, operate, and evolve ML systems in production 

• Solid experience with AWS and MLOps practices, including deployment, monitoring, and operating ML systems at scale 

• Practical experience applying GenAI / LLMs in applied or production contexts, with a clear understanding of trade-offs and limitations 

• Ability to influence technical decisions through clear judgment and collaboration, not formal authority 

• Experience supporting and guiding more junior data scientists through hands-on collaboration, code reviews, and technical feedback 

• Strong sense of ownership and accountability for outcomes, with a pragmatic approach to trade-offs and delivery 

What’s in it for you 

We understand that there is life at work and life outside of work. Here are a few benefits that support us to be our creative best.   

• Gym discounts 
• Employee and Family Assistance program 
• Virtual wellness events 
• Conferences & training budget 
• Regular internal training programs 
• Financial planning with 3% matching Pension  
• Competitive salary 
• Annual bonus structure 

The base salary range for this position is CAD $180k – $120k.

This range reflects the expected compensation at the time of posting. The final offer may vary and can be higher based on relevant skills, experience, location, and market conditions. Based on the role, the total rewards package may also include benefits, bonus, and other employee offerings. 

Use of Artificial Intelligence in Hiring: We use artificial intelligence (“AI”) in our hiring process, including to screen, assess, or select applicants for this position.

Vacancy Status: This job posting is for an existing vacancy. 

At AutoScout24, we’re excited to be hiring for our Canadian company, Trader Corporation - a key part of our international family.

As the Canadian arm of Europe’s largest online car marketplace, Trader Corporation plays a vital role in transforming how people buy, sell, and finance vehicles. With well-known brands like AutoTrader.ca, AutoSync, and Dealertrack Canada, Trader Corporation is driving digital innovation in the automotive industry — now reaching over 25 million Canadians every month.

What You’ll Do 

• Design and build agentic GenAI systems using modern frameworks such as LangChain, AutoGen or Atomic Agents, taking the lead on translating product needs into scalable AI solutions and delivering production-ready implementations.
• Develop and maintain knowledge integration pipelines, including RAG architectures, custom model fine-tuning, vector search, and other grounding methods to ensure our AI systems have the right context for accurate, relevant outputs.
• Define evaluation strategies, build ground-truth datasets, and create automated test and monitoring setups to ensure stable long-term model performance and proactively detect issues such as drift or hallucination.
• Collaborate with engineering, data, and product teams to integrate AI components into platforms, workflows, and customer-facing products, designing clean APIs, robust pipelines, and scalable deployment patterns.
• Act as a hands-on expert for GenAI topics, mentoring peers, guiding solution architecture, and driving best practices in coding, testing, observability, and documentation across the organisation.
• Experiment with new tools, models, and architectures, identify high-impact AI opportunities, and build prototypes that can scale into production-ready solutions. 

What you’ll bring: 

• A degree in computer science, data science, engineering, or a related field.
• Experience building agentic GenAI systems in production (e.g., LangChain, AutoGen, Atomic Agents, or similar frameworks).
• Strong coding skills in Python and experience with robust software engineering practices.
• Practical experience with RAG pipelines, vector databases, embeddings, or fine-tuning workflows.
• Strong understanding of common challenges in AI development (ground-truth evaluation data, monitoring, integration complexity, model drift).
• Experience deploying AI systems in a cloud environment and working with modern ML stacks.
• Familiarity with MLOps, prompt engineering, or LLM-based application design.
• Ability to explain complex AI topics in clear and actionable language to technical and non-technical stakeholders.
• High motivation, ownership mentality, and a strong drive to build impactful AI products.
• Fluency in English; German is a plus. 

The base salary range for this position for Canada is CAD 180K – CAD 200K.

This range reflects the expected compensation at the time of posting. The final offer may vary based on relevant skills, experience, location, and market conditions. Based on the role the total rewards package may also include benefits, bonus, and other employee offerings.

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.

• Strong extended health benefits: Health & Prescription coverage, vision and dental care, virtual health care, out-of-country medical coverage
• Insurance coverage (life, short-term disability, long-term disability, and more)
• Health Care Spending Account
• Two different Employee Assistance Programs
• 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. 

Note: Benefits may vary by location and are subject to local regulations.

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_Vancouver_Canada

About the Data Science Organization 

Northbeam’s Data Science organization serves as the intelligence layer of the company, owning the end-to-end science behind marketing measurement and optimization. This includes developing and advancing our core methodologies—Media Mix Modeling (MMM), Incrementality testing, causal multi-touch attribution (MTA), calibration and validation frameworks, and large-scale experimentation systems. The team is also responsible for AI-driven insights, recommendations, and the creation of reusable, scalable, and rigorously validated scientific systems that power Northbeam’s product and customer value.

About the Role

We are seeking a Staff Data Scientist to advance the statistical and experimentation foundations of Northbeam’s marketing intelligence products, including MMM, Incrementality, Insights, and Recommendation engines.  This is a full-stack data scientist role, operating across the entire lifecycle—from researching and developing advanced statistical and causal inference approaches to implementing, deploying, and maintaining production systems.

You will work at the intersection of R&D and product, owning modeling end-to-end: from data exploration and experimental design to model validation, production integration, and live system iteration. You will bring a deep understanding of statistical modeling techniques and, critically, the assumptions underlying them. This role requires strong judgment in selecting, stress-testing, and adapting models to real-world marketing data where ideal conditions rarely exist.

This is a high-agency, hands-on role, requiring comfort shifting between deep technical work, cross-functional collaboration, and customer-facing problem solving as business needs evolve.

Your Impact

• Develop and evolve statistical and causal inference methodologies that strengthen the rigor and reliability of Northbeam’s marketing measurement products.
• Enhance the accuracy, robustness, and scalability of existing MMM pipelines.
• Write production-quality Python and SQL, collaborating closely with Engineering to integrate statistical workflows into scalable systems.
• Rigorously assess model assumptions, identify potential sources of bias, and implement mitigation strategies.
• Debug data and modeling issues in production and improve the reliability of customer-facing results.
• Translate complex statistical reasoning into clear, decision-ready insights for internal stakeholders and customers.

What You Bring

• Bachelor’s degree in Mathematics, Computer Science, or a highly quantitative STEM field (Master’s preferred).
• 6+ years of applied experience in data science, machine learning, or statistical modeling roles.
• Deep applied experience in statistics and causal inference, including hands-on ownership of experiment design (A/B testing, geo-based experiments, or quasi-experimental methods), power analysis, and interpretation of lift.
• Strong understanding of regression, time series modeling, Bayesian methods, and model evaluation in real-world business settings.
• Experience translating statistical research or experimentation frameworks into production-ready systems.
• Proficiency in Python and SQL, with experience working on modern data platforms and statistical modeling libraries.
• Experience working with production code and comfort making changes to live models and pipelines.
• Interest in (or prior experience with) marketing measurement, including MMM and incrementality, with a strong desire to deepen domain expertise.
• Thrives in a small, fast-paced environment, with the ability to drive projects end-to-end.
• Strong communication skills, with comfort explaining technical concepts to non-technical audiences and supporting customer-facing investigations.
• A growth mindset and genuine curiosity about improving measurement quality and decision-making.

Bonus Skills & Experience

• Experience in marketing attribution, MMM, incrementality, or related marketing measurement challenges.
• Experience with optimization techniques (e.g., linear programming, mixed-integer programming) applied in production systems.
• Familiarity with MLOps practices and data pipeline orchestration tools.
• Startup Experiences.
• PhD in a quantitative field. 

Why Northbeam

Unlike most Series A+ companies, we have a proven business model, strong revenue, and a growing waitlist of customers eager for the products we’re building. We are in a high growth phase and we are nearly profitable.

We sit at the center of the performance-marketing ecosystem with deep partnerships across major ad platforms (Meta, Snap, TikTok, AppLovin, and more). Our unique combination of high-quality partner integrations, rich 1st-party data, and a robust identity graph gives us an advantage that is extremely difficult for competitors to replicate.

Northbeam is where top-tier data talent can directly shape the industry’s most important measurement challenges at scale.

#LI-Remote

ANALYTICS

What We Do

Our Data & Analytics teams build powerful stories and visuals that inform the games we make, the technology we develop, and business decisions that drive Epic.

What You'll Do

We are seeking a Senior Data Scientist to independently own and drive analytics initiatives for Family Experience (FamXP), Investigation analytics and Trust and Safety, with a focus on impacting team and product outcomes. You'll apply your expertise to transform ambiguous business questions into actionable insights while handling highly sensitive data with care and discretion. This role requires leading cross-functional projects, building strong stakeholder relationships across multiple teams, and maintaining the highest standards of data privacy and security. The role is expected to build foundational re-usable data models as well as end reporting and ad hoc analysis to support teams from FamXP, a product team, to Legal.

In this role, you will

• Own and deliver end-to-end analytics projects for Family Experience and Trust & Safety that drive team outcomes and measurably influence product/org outcomes, from problem framing through impact measurement; can range from telemetry implementation to reporting to automation (from Workato to ML)
• Solve ambiguous Family Experience and Trust & Safety problems by designing analyses, evaluating options/tradeoffs, and making independent decisions that keep work moving in a dynamic environment
• Execute team and product/org strategy through analytics planning: translate strategy into metrics, roadmaps/backlogs, and clear success criteria; contribute to setting team goals
• Build and maintain production-quality metrics, dashboards, and data models that monitor safety, parental controls, and age-appropriate experiences across Epic’s ecosystem
• Drive alignment around approach and outcomes with Trust & Safety, Product, Programming, Legal, and Policy partners across the team and organization, managing expectations and trade-offs
• Handle sensitive data related to minors and safety incidents with discretion, applying privacy/security best practices and Epic data governance requirements
• Mentor others on the team and within the product/org: share best practices, review work, and raise the bar for how analytics is done

What we're looking for

• 6-10 years of demonstrated ability to own and deliver analytics projects that execute team outcomes and influence product/org outcomes
• Strong SQL skills (Python, PySpark a plus) and experience working with large-scale datasets; comfort in modern data environments (e.g., Snowflake/Databricks/Spark); familiarity with version control and workflow orchestration tools (Airflow or similar) is a plus
• Proven ability to solve ambiguous problems and make independent decisions on team projects with minimal/no oversight
• Experience turning messy data into production-quality metrics, dashboards, and data models that support operational monitoring and decision-making
• Strong judgment handling sensitive or regulated data; working knowledge of privacy/security practices and relevant compliance concepts
• Ability to execute team + product/org strategy via planning and prioritization; can translate goals into measurable outcomes and help set team goals
• Track record of driving alignment and collaboration across immediate/adjacent teams and the broader product/org
• Clear communicator who can align stakeholders through concise updates and documentation that drive decisions and action
• Evidence of mentoring others on the team/product org (coaching, reviews, raising standards)
• Domain strength in Trust & Safety and/or family experiences online (e.g., moderation, account safety, community health, fraud, or safety feature measurement)

EPIC JOB + EPIC BENEFITS = EPIC LIFE

We pay 100% for benefits for both employees and dependents and offer coverage for supplemental medical, dental, vision, critical illness, telemedicine, Life and AD&D, long term disability insurance as well as weekly indemnity (short term disability) and a retirement savings plan with a competitive employer match. In addition to the EAP (employee assistance program), we also offer a robust mental well-being program through Modern Health, which provides free therapy and coaching for employees & dependents.

As an equal opportunity employer, we celebrate diversity and are committed to creating an inclusive environment for all employees

In this role you may be exposed to adult content

What do we need

We are seeking a Scientific Technical Solutions Lead to join the team developing scientific Solutions built on Dotmatics LUMA, a next-generation, multi-tenant, AI-powered data management and workflow automation for multimodal scientific discovery. As a Scientific technical lead on the team, you will work closely with other Solution Architects, product management, engineering teams, and external stakeholders to deliver exceptional product capabilities via Luma Solutions.

Your focus will be on designing and implementing the configuration necessary to realise product vision and on ensuring that this configuration follows best practices within the Life Sciences and Chemical & Material space.

This role offers the opportunity to shape a foundational part of the modern lab—helping scientists work faster, smarter, and with greater impact.

In this role you will get to:

• Design configuration: Collaborate with Product to determine application structure, define entity/data models, specify task workflows (Scientific Workflows) , and define desired data visualization experiences
• Develop configuration: Create registration entities, data flows, task templates, data visualization experiences, and other configurations in support of developing Luma Solutions that will be delivered as part of the product
• Test and troubleshoot configuration: Perform in-team testing of configuration and assist is handing test cases to the QA group for release testing. Troubleshoot configuration to understand why it is not producing desired results.
• Contribute to documentation: Write draft documentation of configuration and workflows and collaborate with the Documentation team to develop final customer-facing documentation
• Train internal and external users: Train members of other Dotmatics teams and early customers on how to use Luma Solutions configuration and the workflows it supports
• Provide input into new product features: Use new product features in Luma Solutions and provide feedback on the experience, participate in user experience testing, and provide input to the Product team about features that will enable the best Solutions
• Champion quality and best practices: Actively participate in the development of best practices for Luma configuration, and ensure these best practices are followed in the development of Luma Solutions

We are looking for people who have 10+ years of hands-on experience building and delivering informatics solutions for Life Sciences customers. The ideal candidate holds a Bachelor's or advanced degree in Life Sciences, Data Science, Chemistry, Biology, Bioinformatics, or a related technical discipline — and brings a genuine passion for quality and continuous improvement, fueled by a drive to solve problems that truly matter.

The key skills we are looking for: 

• Life Science Industry experience, either as a Scientific Solution Architect, technical application Scientist or a Scientist who has been heavily involved with designing products or technical applications
• Advanced expertise in data modeling, with a proven ability to design robust, scalable data structures
• Expert-level proficiency in configuring low-code platforms and designing end-to-end workflows
• Demonstrated success delivering scientific data platforms or tools spanning data modeling, ETL, APIs, and BI/reporting
• Expert-level SQL skills, with strong working knowledge of Python and JSON
• Deep experience integrating tools and modules to architect complete, cohesive solutions
• Strong analytical ability to translate product requirements into precise technical configuration designs
• Excellent communication skills — able to distill complex technical concepts for both technical and non-technical audiences at all levels
• Experience running and/or supporting scientific workflows in a production or research environment

You may also have 

• Experience running scientific test cases
• Understanding of software testing and or SDLC
• Working knowledge of Databricks
• Drug Discovery or Biotechnology industries or Other scientific Industries

About Life360

Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app,Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with emergency dispatch. Life360 serves approximately 95.8 million monthly active users (MAU), as of December 31, 2025, across more than 180 countries.

Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US and Canada) regardless of any specified location above. 

We are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About The Team

Data Science at Life360 is a lean, high-impact, matrixed team with individuals embedded in business units and working cross-functionally with Product, Analytics, Engineering, and business stakeholders. We are dedicated to enhancing and optimizing the user experience, accelerating growth, and generating revenue through subscriptions, partnerships, and ads. We leverage a variety of technical skills and tools including experimentation, machine learning, advanced analytics, and agentic AI (AI-Native development) to deliver exceptional customer value.

About the Job

We are seeking a Senior Data Scientist to scale Life360’s growth and user retention efforts. This role will be a core contributor to the Growth team’s strategy and operations. You will work closely with business leads, lifecycle marketing, and user acquisition teams to optimize the entire funnel—from registrations to subscriptions and churn reduction. Your expertise will help Life360 make smarter, faster, and more scalable decisions, directly impacting millions of users.

This role requires strong technical expertise and practice experience in machine learning, statistical modeling, experimentation, and causal inference, as well as the ability to collaborate with cross-functional teams to drive measurable business outcomes.

For candidates based in the US, the salary range for this position is $129,000 to $190,000 USD. For candidates based out of Canada, the salary range for this position is $149,500 to $176,000 CAD. We take into consideration an individual's background and experience in determining final salary - therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity.

What You’ll Do

• Experimentation & Causal Inference: Design and implement scalable A/B tests to train causal inference models and multi-armed bandits to optimize registration, trial conversion, and retention strategies.
• Automation & Personalization: Build and scale automation tools for experimentation and segmentation, ensuring teams can efficiently test and iterate on hypotheses.
• Growth Optimization: Develop predictive models and statistical frameworks to improve trial-to-subscription conversion, reduce churn, and enhance overall customer LTV.
• User Segmentation & Personalization: Leverage clustering, behavioral analysis, and geospatial data to identify key user segments and tailor experiences accordingly.
• Product Development: Collaborate with product managers and engineers to conceive and develop innovative product ideas, driving feature iteration and development to make impact.
• Cross-functional Collaboration: Partner closely with growth, lifecycle marketing, and user acquisition teams to translate insights into scalable marketing and product strategies.
• Data Infrastructure & Tooling: Work with data engineering to improve the data ecosystem, ensuring robust, scalable pipelines for experimentation and analysis.
• Thought Leadership: Act as a mentor and thought leader within the data science team, helping to define best practices in experimentation, machine learning, data-driven decision-making, and agentic AI (AI-Native) best practices.

What We’re Looking For

Desired Experience & Qualifications

• 4+ years of experience in data science, machine learning, or analytics, with a focus on growth, experimentation, and user retention.
• Strong experience in causal inference, A/B testing methodologies, and statistical modeling.
• Deep understanding of machine learning models for user segmentation, personalization, and predictive analytics.
• Proficiency in Python (Pandas, Scikit-learn, PyTorch, or TensorFlow) and SQL for data manipulation and analysis.
• Experience with big data technologies such as Spark, AWS, Databricks.
• Experience with product development or customer life cycle management.
• Strong business acumen with the ability to translate data insights into actionable business strategies.
• Excellent communication and leadership skills, with the ability to influence cross-functional teams.
• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field

Preferred Qualifications

• Experience in subscription-based products, lifecycle marketing, or user acquisition.
• Experience with geospatial data and mobile location-based services.
• Familiarity with Bayesian modeling, uplift modeling, and reinforcement learning for experimentation.
• Experience with workflow automation tools for experimentation and data science operations.
• Experience in the consumer technology sector, particularly within a fast-paced and sometimes ambitious development setting.

Core Expectations

• Problem-solving mindset - You structure ambiguous problems precisely before reaching for a tool, AI or otherwise
• Collaborative approach - You can explain technical tradeoffs and articulate ideas effectively, work well across teams, and value diverse perspectives
• Ownership mentality - You take responsibility for your work from design through production and beyond
• AI-native working style - You use AI tooling (Claude Code or equivalent) as a genuine development partner: delegating discrete tasks, reviewing outputs critically, and running parallel workstreams rather than hand-holding one agent at a time

We believe culture fit and problem-solving ability matter more than checking every technical box. We're happy to help you grow into areas where you have less experience.

Our Benefits

• Competitive pay and benefits.
• Medical, dental, vision, life and disability insurance plans (100% paid for US employees). We offer supplemental plans for medical and dental for Canadian employees.
• 401(k) plan with company matching program in the US and RRSP with DPSP plan for Canadian employees.
• Employee Assistance Program (EAP) for mental wellness.
• Flexible PTO and 12 company wide days off throughout the year.
• Learning & Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership for your preferred circle.

Life360 Values

Our company’s mission driven culture is guided by our shared values to create a trusted work environment where you can bring your authentic self to work and make a positive difference 

• Be a Good Person - We have a team of high integrity people you can trust. 
• Be Direct With Respect - We communicate directly, even when it’s hard.
• Members Before Metrics - We focus on building an exceptional experience for families. 
• High Intensity High Impact - We do whatever it takes to get the job done. 

Our Commitment to Diversity

We believe that different ideas, perspectives and backgrounds create a stronger and more creative work environment that delivers better results. Together, we continue to build an inclusive culture that encourages, supports, and celebrates the diverse voices of our employees. It fuels our innovation and connects us closer to our customers and the communities we serve. We strive to create a workplace that reflects the communities we serve and where everyone feels empowered to bring their authentic best selves to work.

We are an equal opportunity employer and value diversity at Life360. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status or any legally protected status.  

We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Even if you don’t meet 100% of the below qualifications, you should still seriously consider applying!

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About the job

Do you think like a management consultant, thrive in a startup environment, and can’t stop thinking about the intersection of data, technology, and marketing?

With over 2000 employees, offices on five continents, and world-class clients like Samsung, L’Oreal, and Mattel, Artefact is a consulting firm that transforms data into value and business impact. We’ve recently launched in the US with offices located in NYC and Los Angeles, and we want you to join us as an integral part of our founding team!

Who We Are

Founded and headquartered in Paris, Artefact is a next-generation consulting firm, specializing in data, analytics & AI consulting, dedicated to transforming data into business impact across the entire value chain of organizations. We are proud to say that we help our clients grow their data and digital capabilities, and that we’re also growing in parallel.

We have 2000 employees across 34 offices who are focused on accelerating digital transformation. Our state-of-the-art data technologies, lean AI agile methodologies, and cohesive teams of the finest business consultants, data analysts, data scientists, data engineers, and digital experts are all dedicated to bringing extra value to every client. We design data-based solutions to meet our clients' specific needs, always conceived with a business-centric approach and delivered with tangible results. Our data-driven services are built upon the deep AI expertise we've acquired with our 1000+ client base around the globe.

Find out more at artefact.com.

What you will be doing 

In addition to the core Data Science and ML Engineering Team, you will work with different stakeholders to:

• Translate marketing and business challenges into analytical use cases, assess feasibility, and define clear hypotheses.
• Develop statistical and machine learning models including regression, forecasting, classification, and clustering to identify performance drivers and predict business outcomes.
• Build and maintain scalable data pipelines for data ingestion, transformation, and quality assurance across diverse marketing data sources.
• Develop production ready modeling solutions including model training, deployment, monitoring, and ongoing refinement.
• Evaluate and select appropriate statistical and machine learning techniques based on business context, constraints, and data availability.
• Create clear and compelling data visualizations and dashboards to support data storytelling and decision making.
• Collaborate with cross functional partners in an agile environment and iterate on solutions to maximize business impact.

What we are looking for 

• The ideal candidate has a substantial quantitative skill set with 5+ years of relevant experience. 
• Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field.
• Excellent interpersonal and communication skills
• Strong knowledge of data science algorithms and at least one proven experience in developing Statistical and ML algorithms
• Proficient in Python (preferred) and/or R

Preferred: 

• Financial sector experience. 
• Preference in Causal Inference topics, Time Series, Advanced Statistics
• Cloud technologies (GCP, Azure, AWS) especially Google Cloud Platform

Why you should join us

• We are united by our values and strengthened by our hybrid expertise.
• There is always a way: We're from the breed of does, of diggers, of makers. Because ideas are valuable only if executed.
• Client trust is won on the field: Addressing client needs flows better hands on at their side.
• If not used, it is useless: Our love for technology translates into a steep desire for adoption, true brilliance is about impact.
• If not shared, our work is not done: Sharing knowledge is the best way to button up a mission, benefitting clients and colleagues.
• We learn everyday: Tech is a land where everything move at the speed of light, you better be ready to challenge yourself.