data scientist, product analytics

2026 phd scientist intern (driver pricing), us Jobs in San Francisco

2026 summer intern - public affairs & access: patient strategy Jobs in San Francisco

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applied scientist, marketing measurement Jobs in San Francisco

applied scientist, marketing measurement

2026 phd scientist intern driver pricing us

Uber

<div>We are looking for current students to join Uber as Scientist Interns for 12 weeks in Summer 2026. As an intern, you will be embedded in a product team working on solving real-world Uber problems under the supervision of an analyst on that team, and will have the opportunity to partner closely with Scientists, Software Engineers, Product Managers, and other cross functional partners.
 
 
About the Role
 
 
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked? If so, Uber is for you. In our Sciences division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
 
 
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
 
 
About the Team
 
 
The Driver Pricing team is looking for talented data scientists to help us tackle some of the most challenging and interesting problems at Uber. In this role, you will apply your quantitative skills in machine learning, statistics, and economics to improve the Uber user experience and the overall marketplace performance. You'll be a key contributor to the team that designs, evaluates, and builds our systems for pricing trips for drivers.
 
 
What You'll Do
<ul><li>Work with a mentor closely to define a business problem, scope a project, develop, and prototype the solution using data-driven approaches
</li><li>Work with engineers and product managers to turn prototypes into scalable solutions
</li><li>Present findings to leaders to inform decisions
</li><li>Establish standard methodologies for science such as modeling, coding, analytics, optimization, and experimentation
</li><li>Conduct experiments to drive business decisions
</li></ul>Basic Qualifications
<ul><li>Pursuing a Ph.D. majoring in Economics, Operations Research, Mathematics, Computer Science, Statistics, Machine Learning, or other related quantitative fields. Candidates should have at least one semester/quarter left of their education after finishing the internship
</li><li>Strong problem solving and analytical abilities
</li></ul>Preferred Qualifications
<ul><li>Coding proficiency in areas such as R, Spark, SQL, Python and AB Testing
</li><li>Background in data visualization via open-source libraries/packages or third-party tools (i.e. Tableau, Mixpanel, Looker, or similar)
</li><li>Knowledge of underlying mathematical foundations of statistics, machine learning, optimization, stochastic processes, economics, and analytics
</li><li>Experience in the following areas: Exploratory Data Analysis, Statistical Analysis, Model Development, Operations Management, Revenue Management and Pricing, Advertising, Experimental Design, Assortment Planning, Transportation
</li><li>Organized, detail oriented and able to work independently on multiple projects at once
</li><li>Ability to communicate effectively with both technical and business partners
</li><li>Open to feedback, excellent at implementing newly learned ideas and concepts
</li><li>Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation
</li>Independence, self-starter mindset, excellent communication, and outstanding follow-through - you energetically tackle your work and love the responsibility of being individually empowered 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits.</div>

2026 PhD Scientist Intern (Driver Pricing), US

General Medicine

<div><h1 class="jobSectionHeader">Marketplace Scientist
</h1><h1 class="jobSectionHeader">About General Medicine</h1>
We&rsquo;re building a platform that makes it delightfully simple for people to find, book, and afford care across virtual and in-person visits, prescriptions, labs, imaging, and more.
As a Marketplace Scientist at General Medicine, you&rsquo;ll work directly with our Chief Economist to design the algorithms, mechanisms, and models that underpin the matching, pricing, and insurance estimation systems at the heart of the business. From understanding patient preferences to forecasting prices across complex insurance networks, your work will determine how the marketplace functions and scales.<h2 class="jobSectionHeader">
What we&rsquo;re looking for</h2>
As a Marketplace Scientist at General Medicine, you&rsquo;ll work directly with our Chief Economist to design the algorithms, mechanisms, and models that underpin the matching, pricing, and insurance estimation systems at the heart of the business. From understanding patient preferences to forecasting prices across complex insurance networks, your work will determine how the marketplace functions and scales.<h2 class="jobSectionHeader">
You should be excited to:</h2><ul><li>
Own our insurance price estimation system end to end &ndash; defining the roadmap, identifying and acquiring new data sources, and moving us from a rules-based engineering solution to a Bayesian statistical model that returns calibrated estimates with confidence intervals even where data is incomplete.</li><li>
Translate statistical models into concrete product milestones, sequencing the work across incremental launches and collaborating with engineering to get things into production.</li><li>
Work with rich but messy operational datasets &ndash; cleaning, joining, interpreting, and stress-testing them &ndash; and make the case for investing in new external sources where the evidence supports it.</li><li>
Rebuild forecasting infrastructure that is currently limited, supporting capacity planning, patient routing, and network design.</li><li>
Run counterfactual analyses and empirical studies to validate model designs and inform decisions on ad spend, utilisation, and patient direction.</li></ul><h2 class="jobSectionHeader"> 
Ideal Qualifications</h2><ul><li>
4&ndash;7 years of experience in a quantitative field (Statistics, Economics, Math, Computer Science, Physics, or similar)</li><li>
Undergraduate degree with strong quantitative rigor (economics, applied math, engineering, computer science, physics, or similar); Master&rsquo;s or PhD preferred</li><li>
Advanced fluency in Python or R, including experience working with large, messy datasets and building production-quality analyses</li><li>
Comfort with at least one programming or analytical tool beyond SQL/Excel (e.g., Python, R, dbt, BI tooling)</li><li>
Strong statistical intuition and ability to reason from first principles</li><li>
Experience building production-facing models or decision systems, not just exploratory analyses</li><li>
Comfort working with large, imperfect real-world datasets such as insurance claims or reimbursement files</li><li>
A clear, demonstrated history of academic and professional excellence</li><li>
High ownership and ability to operate in ambiguous, fast-moving environments</li><li>
Startup-ready mindset: resourceful, hands-on, and energized by ambiguity.</li></ul>
This is a hybrid role in either SF or Boston (Cambridge).</div>

Marketplace Scientist

Genentech

<div><div><div>THE POSITION</div>
2026 Summer Intern - Public Affairs &amp; Access: Patient Strategy
Department Summary
Public Affairs &amp; Access is a multi-disciplinary organization that includes Access Solutions &amp; Patient Support; Channel &amp; Contract Management; Corporate Communications; External Affairs; Patient Strategy; Policy, Evidence, &amp; Access Strategy; and Strategic Business Operations. Our mission is to drive positive change in the healthcare system so that every patient can access our science. We lead the development of meaningful partnerships, forward-looking pricing, contracting and distribution strategies, and proactive policy solutions that advance a more equitable and hopeful future for all of those who need our therapies.
This position is based in South San Francisco, CA, On-Site.
The Opportunity
Patient Strategy is looking for an intern to help evolve the design and execution in one of the key workstreams, digital first patient experience. We anticipate that the intern will be working closely with the team performing data analysis to assess feasibility of predictive use cases and AI agents to support the future state patient capabilities.<ul><li>
Working with the business users to ensure use cases documented and reflected in design</li><li>
Partnering with Activation and tech teams to design and test AI agents to support human agent workflow</li><li>
Develop recommendations for patient strategy roadmapping in collaboration with business owners and leads</li></ul>
Program Highlights<ul><li>
 Intensive 12-weeks , full-time (40 hours per week) paid internship.</li><li>
Program start dates are in May/June (Summer)</li><li>
A stipend, based on location, will be provided to help alleviate costs associated with the internship.</li><li>
Ownership of challenging and impactful business-critical projects.</li><li>
Work with some of the most talented people in the biotechnology industry.</li></ul>
Who You Are (Requirements)
Required Education: You meet one of the following criteria:<ul><li>
Must be pursuing a Bachelor's degree
</li><li>Must have attained a Bachelor's degree (recent graduates not currently enrolled in a grad program)</li></ul>
Required majors: Biomedical/Health Informatics, Data Science, Computer Science, Business Analytics or Biomedical Engineering.
Required Skills:<ul><li>
Excellent communication, collaboration, and interpersonal skills.</li><li>
Complements our culture and the standards that guide our daily behavior &amp; decisions: Integrity, Courage, and Passion</li><li>
Analytical Proficiency, AI/ML knowledge</li><li>
Workflow design: Ability to map complex human-computer workflows and document use cases clearly.</li></ul>
Relocation benefits are not available for this job posting.
The expected salary range for this position based on the primary location of South San Francisco, CA is $24- $33/hour. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. This position also qualifies for paid holiday time off benefits.
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Internships &amp; Co-ops
</div><div>Schedule
Full time
</div><div>Job Type
Temporary (Fixed Term)
</div><div>Posted Date
Mar 10th 2026
</div><div>Job ID
202603-106291</div></ul></div></div></div></div>

2026 Summer Intern - Public Affairs & Access: Patient Strategy

<div>About the Role
 
 
Have you ever ordered a car service on Uber, and when the ride arrives, wondered how it got to you so fast? Ever ordered food on UberEats and wondered where the driver was before receiving your order and how long it took to get to the restaurant or if your order was ready when the courier arrived? Ever wondered why your grocery delivery from Uber always has the best apple picked?
 
 
If so, Uber is for you. In our ML and Science division, we strive to make magic within Uber's marketplace. This requires judgment to make difficult trade-offs, blending algorithms with human resourcefulness, and the ability to build simplicity from complexity. When we get the balance right for everyone, Uber magic happens. We build systems to peer into the future to craft the most cost-efficient marketplace for matching supply and demand. We are passionate about using innovative economics, machine learning, and scalable distributed software that automates and optimizes every aspect of this intricate dance between participants of the marketplace.
 
 
We are involved in every stage of the product development cycle and use data to inform product decisions, build models to power our solutions, and also develop platform tools that are used across teams with a primary focus on Mobility and Delivery. We work with millions of earners across the globe to make this magic happen and want you to join us!
 
 
About the Team
 
 
Earners (drivers and couriers) are an integral part of Uber's multi-sided marketplace. They provide the time and the means to move people and things. Importantly, they enable the connection between the physical and digital world to make the movement happen at the push of a button for everyone, everywhere.
 
 
Within Uber, Earner plays a critical role in earners' journey as the team is responsible for earner onboarding, activation, early life cycle, and resurrection. This presents the teams with the opportunity to shape and tailor the product experience during earners' many firsts (i.e., first time interacting on the Uber platform, choosing the earning opportunity, going online, receiving incentive offers, completing a trip, or reading the earnings summary). These firsts can be daunting.
 
 
Therefore, making sure that the earner journey is great at every touch point is important to build trust with Earners, communicate Uber's value proposition, and ensure each firsts to be a great experience.
 
 
The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
 
 
What the Candidate Will Need / Bonus Points
- What the Candidate Will Do - 
 
 
<ul><li>Build statistical, optimization, and machine learning models
</li><li>Develop innovative new earner incentives that earners for choosing our network and optimizing Uber's new earner incentives spend
</li><li>Optimize Uber's background check spend and onboarding funnel
</li><li>Design recommendation engines to recommend the most relevant earning opportunities and early lifecycle content
</li><li>Develop matching algorithms for driver to driver mentorship program
</li><li>Model and predict earner behaviors to improve earner experience throughout the onboarding funnel
</li><li>The team employs a variety of ML/AI techniques, spanning from causal ML meta learners, supervised ML, RL multi-armed bandits, genAI LLMs, transformer modeling on sequential data to deep learning embeddings to build impactful data products.
</li><li>Work closely with multi-functional leads to develop technical vision, new methodological approaches, and drive team direction.
</li><li>Collaborate with cross-functional teams such as product, engineering, operations, and marketing to drive ML system development end-to-end from conceptualization to final product.
</li></ul>- Basic Qualifications - 
 
 
<ul><li>PhD, Master or equivalent experience in Computer Science, Machine Learning, Operations Research, Statistics, or other related quantitative fields or related field
</li><li>2 years minimum of industry experience as a Machine Learning Engineer/Research Scientist with a strong focus on deep learning and probabilistic modeling.
</li><li>Proficiency in multiple object-oriented programming languages (e.g. Python, Go, Java, C++).
</li><li>Experience with any of the following: Spark, Hive, Kafka, Cassandra.
</li><li>Experience building and productionizing innovative end-to-end Machine Learning systems.
</li><li>Experience in exploratory data analysis, statistical modeling, hypothesis testing, and experimental design.
</li><li>Experience working with cross-functional teams(product, science, product ops etc).
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>3+ years of industry experience in machine learning, including building and deploying ML models.
</li><li>Publications at industry recognized ML conferences.
</li><li>Experience in modern deep learning architectures and probabilistic modeling.
</li><li>Experience with optimization techniques, including reinforcement learning (RL), Bayesian methods, causal ML meta learners, genAI LLM.
</li>Expertise in the design and architecture of ML systems and workflows. 
<li>
</li></ul> 
 
 
 
For New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Machine Learning Engineer II

<div>About the Role
 
 
We are looking for a data scientist who combines strong quantitative rigor with a deep interest in human behavior. This role sits at the intersection of business analytics consulting and employee listening, shaping company-wide decisions through advanced analytics, survey insights, and behavioral data.
 
 
Role and Responsibilities
 
 
Drive company-level workforce strategy
 
<ul><li>Lead high-impact analytics that inform strategic decisions on engagement, retention, performance, and organizational health
</li><li>Translate ambiguous business questions into structured analytical frameworks and measurable outcomes
</li></ul> 
Apply advanced quantitative methods to people data
 
<ul><li>Use statistical modeling, causal inference, experimentation, and/or machine learning to understand employee behavior and outcomes
</li><li>Work with messy, real-world people data and integrate multiple data sources (survey, HRIS, behavioral data)
</li></ul> 
Evolve employee listening analytics
 
<ul><li>Analyze Uber-wide survey data and behavioral signals (e.g., organizational network analytics)
</li><li>Improve measurement approaches (survey design) and uncover actionable insights on employee experience
</li></ul> 
Influence stakeholders at all levels
 
<ul><li>Communicate complex findings clearly to both technical and non-technical audiences
</li>Act as a thought partner to senior leaders, shaping decisions with data-backed recommendations 
<li>
</li></ul> 
 
What the Candidate Will Need / Bonus Points
- Basic Qualifications - 
 
 
<ul><li>Master's or PhD in a quantitative field (e.g., I/O Psychology, Organizational Behavior, Behavioral Economics, Statistics, Data Science, or related)
</li><li>Proficiency in SQL
</li>2+ years of industry experience using Python or R to analyze large-scale datasets 
<li>
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>PhD with 1+ years, or MS with 3+ years of experience in applied research or data science (ideally in a fast-paced, tech environment)
</li><li>Strong foundation in statistical modeling, causal inference, experimentation, and/or machine learning
</li><li>Background in people analytics, HR data, or behavioral science applications
</li><li>Experience with survey design and measurement, and/or organizational network analysis (ONA)
</li>Demonstrated ability to leverage GenAI tools to automate, augment, or scale data analysis, insight generation, or research workflows 
<li>
</li></ul> 
 
 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Data Scientist, People Analytics

<div>About the Role
 
 
The fares platform team powers the fares for all of Uber - that's all riders, earners and eaters across the Uber and Uber Eats app. With $190B+ in gross bookings processed by the fares platform annually, we solve high impact problems that are critical to Uber's success.
 
 
As a Scientist on this team, you will leverage experiment design, exploratory data analysis, causal inference and model development to solve a wide variety of problems in domains like pricing, policy design, optimization and defect reduction.
 
 
What the Candidate Will Need / Bonus Points
 
 
What the Candidate Will Do: 
 
 
<ul><li>Refine ambiguous questions and generate data backed hypotheses through a deep understanding of the data, systems, customers and business.
</li><li>Use experiments and causal inference methods to validate the hypothesis and drive business goals critical to Uber's success.
</li><li>Act as a thought partner with cross-functional teams across various disciplines, including product, engineering, and operations, to drive product strategy. Influence the product roadmap for fares and several cross-organizational teams.
</li><li>Build ML models to solve complex problems and create AI agents to automate data science workflows.
</li>Communicate findings clearly to technical and non-technical leadership to influence decisions and product direction. 
<li>
</li></ul> 
 
Basic Qualifications: 
 
 
<ul><li>Ph.D., M.S., or Bachelors degree in Statistics, Economics, Machine Learning, Computer Science, or other quantitative fields.
</li><li>Minimum 5 years of industry or academic experience as an Applied or Data Scientist or equivalent (with at least two of those years in industry).
</li><li>Experience with experiment design, exploratory data analysis, causal inference and model development.
</li>Proficient in both a data ETL language (e.g. SQL) and a scripting language (e.g. Python, R). 
<li>
</li></ul> 
 
Preferred Qualifications:
 
<ul><li>Minimum 7 years of industry experience as an Applied or Data Scientist or equivalent.
</li><li>Experience using statistical methodologies in platform, marketplace or consumer domains.
</li><li>Demonstrated ability to leverage data and systems thinking for storytelling and root cause analysis.
</li>Excellent communication skills: able to lead initiatives across multiple product areas and communicate findings with leadership. 
<li>
</li></ul> 
 
For New York, NY-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For Seattle, WA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For Sunnyvale, CA-based roles: The base salary range for this role is USD$190,000 per year - USD$211,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Senior Scientist, Fares

<div>About the Role
 
 
As an Applied Scientist on the incrementality foundations team within marketing measurement, you will contribute to Uber Marketing Org's commitment to science-backed decision making. This team is responsible for building experiment forms, models, &amp; processes for turning complex hypotheses into reliable, actionable incrementality signals that inform planning, forecasting, and investment decisions across the business. Your work will focus on building robust processes for interpreting measurement data, building foundational models for estimation &amp; inference, and researching experimentation best practices for accurate and complete incrementality measurement. Your work will inform smarter investment and decision-making systems across Uber's Brand and Performance Marketing. This team sits close to production systems, partnering with Product, Engineering, and cross-functional Science teams to ensure incrementality measurement is rigorous, scalable, and decision-ready
 
 
What the Candidate Will Need / Bonus Points
<ul><li>Develop and apply statistical and causal inference models to estimate the incremental impact of marketing across channels, markets, and test designs.
</li><li>Design custom tests &amp; analyze results from complex experiments, including multi-cell, market-level, and longitudinal tests.
</li><li>Contribute to foundational modeling efforts such as hierarchical smoothing, aggregation across tests, and handling of low-signal or sparse data.
</li><li>Assist in research on advanced topics, including learning elasticity with experiments and analyzing event relationships to improve experiment accuracy and interpretation.
</li><li>Partner with Product and Engineering to integrate incrementality models into reporting and decision-making workflows
</li><li>Research and help establish best practices for experiment design, post-analysis interpretation, and measurement tradeoffs.
</li><li>Collaborate with other Applied Science and Data Science teams to align incrementality outputs with broader measurement and investment frameworks.
</li></ul>Basic Qualifications
<ul><li>Bachelor's degree or higher in a quantitative field such as Statistics, Economics, Mathematics, Computer Science, or a related discipline.
</li><li>2+ years of experience applying statistical and causal inference methods to real-world data in an applied setting.
</li><li>Strong foundation in statistical modeling, hypothesis testing, and experimental design, including A/B testing, incrementality, or quasi-experimental methods.
</li><li>Hands-on experience designing, analyzing, and interpreting experiments, including evaluation of uncertainty, limitations, and tradeoffs.
</li><li>Proficiency in Python or R and SQL for analyzing and modeling large, complex datasets.
</li><li>Experience working with marketing, growth, advertising, or similar business domains where measurement and investment decisions are central.
</li><li>Ability to clearly communicate analytical insights to technical and non-technical stakeholders and collaborate effectively in cross-functional teams.
</li><li>Demonstrated ability to collaborate effectively in cross-functional, fast-moving environments.
</li></ul>Preferred Qualifications
<ul><li>Bachelor's, Master's or PhD in a quantitative discipline (e.g., Statistics, Economics, Mathematics, Computer Science), or equivalent applied industry experience.
</li><li>Experience with advanced statistical or modeling techniques such as hierarchical / multi-level models, time-series analysis, or meta-analysis.
</li><li>Experience with incrementality testing, geo-experiments, or marketing measurement use cases (e.g., attribution, MMM, or related frameworks).
</li><li>Familiarity with marketing investment concepts such as elasticity, budget allocation, or cross-channel tradeoffs.
</li><li>Experience contributing to shared codebases or production-adjacent analytics systems, including collaboration with Product or Engineering partners.
</li><li>Ability to independently drive scoped projects end-to-end with guidance, and operate effectively in ambiguous or evolving problem spaces.
</li>Curiosity and learning mindset, with demonstrated ability to ramp quickly on new domains, tools, or methodologies. 
<li>
</li></ul> 
 
For New York, NY-based roles: The base salary range for this role is USD$161,000 per year - USD$179,000 per year. For San Francisco, CA-based roles: The base salary range for this role is USD$161,000 per year - USD$179,000 per year. For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Applied Scientist, Marketing Measurement

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