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applied scientist marketing measurement

Uber

<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

<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

SoFi

<div>
 
 Employee Applicant Privacy Notice
 
 
 
 
 Who we are:
 
 
 
 Shape a brighter financial future with us.
 
 
 Together with our members, we&rsquo;re changing the way people think about and interact with personal finance.
 
 
 We&rsquo;re a next-generation financial services company and national bank using innovative, mobile-first technology to help our millions of members reach their goals. The industry is going through an unprecedented transformation, and we&rsquo;re at the forefront. We&rsquo;re proud to come to work every day knowing that what we do has a direct impact on people&rsquo;s lives, with our core values guiding us every step of the way.
 
 Join us to invest in yourself, your career, and the financial world.
 
 
 
 
 The role:
 
 
 
 SoFi is seeking a highly motivated Data Scientist to join the Marketing Data Science (MDS) team. The MDS team plays a crucial role in enabling data-driven decisions across SoFi's Marketing organization through robust analytics, modeling, experimentation, and measurement.
 
 
 This exciting new role will be part of the Optimization hub and will support both TV/DV media-specific optimization and broader marketing budget planning, with roughly half of the work focused on media analytics, forecasting, and optimization, and the other half focused on holistic marketing budget forecasting and scenario planning across brand, sponsorships, product marketing, and all marketing channels (TV, DV, DM, social, display etc.).
 
 
 The role is execution-focused, with ownership of recurring analytical deliverables and workflows. The IC2 will work closely with senior data scientists and marketing stakeholders, with a clear growth path toward independently owning forecasting, optimization analyses, and stakeholder partnerships over time.
 
 
 
 What you&rsquo;ll do:
 
 
 
 
 <ul>
 <li>
 Own and maintain recurring dashboards and analytical deliverables that support media performance monitoring and broader marketing spend diagnostics across channels.
 </li>
 <li>
 Partner with Media, Brand Marketing, and Product Marketing to support day-to-day analytics, deep dives, and planning-related questions.
 </li>
 <li>
 Support quarterly and annual marketing forecasts using SoFi&rsquo;s in-house Marketing Mix Modeling (MMM) and related forecasting frameworks.
 </li>
 <li>
 Run MMM pipelines and refreshes, including data preparation, quality checks, model execution, and output validation.
 </li>
 <li>
 Assist in interpreting MMM outputs and translating results into insights that inform media and marketing investment decisions.
 </li>
 <li>
 Support media allocation and optimization analyses (e.g., TV vs. Digital, upper- vs. lower-funnel tradeoffs), including scenario modeling and sensitivity analysis.
 </li>
 <li>
 Contribute to holistic marketing budget optimization and scenario planning across brand, sponsorships, product, and performance marketing investments.
 </li>
 <li>
 Support cross-channel budget tradeoff analyses to evaluate the impact of spend shifts across media types and marketing initiatives.
 </li>
 <li>
 Contribute to ongoing improvement of MMM models and forecasting tools, including feature development, testing, automation, and documentation.
 </li>
 <li>
 Collaborate closely with senior data scientists to improve forecast accuracy, model robustness, and the usability of optimization outputs for stakeholders.
 </li>
 <li>
 Maintain clear documentation of models, assumptions, and analytical workflows to support long-term maintainability.
 
 
 
 </li>
 </ul>
 
 What you&rsquo;ll need:
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related quantitative field.
 </li>
 <li>
 2&ndash;4 years of experience in data science, analytics, or applied modeling roles supporting marketing, media, growth, or product analytics.
 </li>
 <li>
 Strong proficiency in SQL and Python, with experience building analytical workflows and working with large, structured datasets.
 </li>
 <li>
 Experience with forecasting, causal modeling, or Marketing Mix Modeling (MMM), including running model pipelines and supporting model interpretation.
 </li>
 <li>
 Familiarity with marketing performance measurement across a broad range of channels, including upper- and lower-funnel investments.
 </li>
 <li>
 Experience building and maintaining dashboards or recurring analytical deliverables using BI tools (e.g., Tableau or equivalent).
 </li>
 <li>
 Comfort working in a production analytics environment, including data validation, model QA, and ongoing maintenance.
 </li>
 <li>
 Ability to translate analytical results into clear insights for non-technical stakeholders, with support from senior team members.
 </li>
 <li>
 Strong attention to detail, structured problem-solving skills, and comfort working with ambiguous planning questions.
 </li>
 <li>
 Collaborative mindset and ability to work effectively with cross-functional partners across Marketing.
 </li>
 <li>
 Curiosity and motivation to grow toward greater ownership of forecasting, optimization, and stakeholder-facing work over time.
 
 
 
 </li>
 </ul>
 
 Compensation And Benefits
 
 
 
 The base pay range for this role is listed below. Final base pay offer will be determined based on individual factors such as the candidate&rsquo;s experience, skills, and location.
 
 
 To view all of our comprehensive and competitive benefits, visit our
 
 Benefits at SoFi
 
 page!
 
 
 SoFi provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion (including religious dress and grooming practices), sex (including pregnancy, childbirth and related medical conditions, breastfeeding, and conditions related to breastfeeding), gender, gender identity, gender expression, national origin, ancestry, age (40 or over), physical or medical disability, medical condition, marital status, registered domestic partner status, sexual orientation, genetic information, military and/or veteran status, or any other basis prohibited by applicable state or federal law.
 
 
 The Company hires the best qualified candidate for the job, without regard to protected characteristics.
 
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 New York applicants: Notice of Employee Rights
 
 
 SoFi is committed to an inclusive culture. As part of this commitment, SoFi offers reasonable accommodations to candidates with physical or mental disabilities. If you need accommodations to participate in the job application or interview process, please let your recruiter know or email accommodations@sofi.com.
 
 
 Due to insurance coverage issues, we are unable to accommodate remote work from Hawaii or Alaska at this time.
 
 
 
 Internal Employees
 
 
 
 If you are a current employee, do not apply here - please navigate to our Internal Job Board in Greenhouse to apply to our open roles.
</div>

Marketing Data Scientist, Optimization

Pinterest

<div>
 
 About Pinterest
 
 
 
 Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we&rsquo;re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.
 
 
 Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other&rsquo;s unique experiences and embrace the flexibility to do your best work. Creating a career you love? It&rsquo;s Possible.
 
 
 At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we&rsquo;re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we&rsquo;ll explore your foundational skills and how you collaborate with AI.
 
 
 Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here.
 
 
 We are looking for a Data Scientist to join our marketing org. As a Data Scientist you introduce greater scientific rigor into the marketing measurement and optimization processes to shape Pinterest&rsquo;s revenue growth and marketing strategy. The results of your work will influence and drive strategic decisions for the company - identify investment opportunities for growth, understand revenue growth and behavior, and define metrics to grow and sustain our advertiser base. You will collaborate on a wide array of business problems with a diverse set of cross-functional partners across Marketing, Product, Engineering, Analytics and others.
 
 
 The role is within the Marketing team and would be supporting business marketing efforts focused on driving revenue growth for Pinterest.
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Lead the design, implementation, and continuous improvement of advanced marketing measurement frameworks and statistical models to quantify marketing ROI. Marketing channels could be different paid media, organic social, email, in person events, webinars, elearning platform etc.
 </li>
 <li>
 Build and deploy statistical and machine learning models such as propensity, forecasting, and lifetime value (LTV) models&mdash;to optimize marketing strategies and enhance audience targeting.
 </li>
 <li>
 Develop and refine attribution methodologies to evaluate the effectiveness of marketing initiatives across multiple channels.
 </li>
 <li>
 Assess the incremental impact of marketing activities using causal inference techniques and testing/experiment frameworks.
 </li>
 <li>
 Conduct deep, strategic analyses to address key business questions, such as how to improve marketing ROI, how to improve marketing budget allocation to optimize the business impact, measuring the impact of marketing in both mature and new markets, identifying opportunities to increase advertiser growth and revenue through marketing initiatives
 </li>
 <li>
 Translate complex analytical findings into clear, actionable insights and strategic recommendations for both technical and non-technical stakeholders, including senior leadership.
 </li>
 <li>
 Design, maintain, and promote dashboards and automated reporting tools to empower stakeholders with self-serve, data-driven decision-making capabilities. Build and optimize ETL data pipelines to automate reporting, support deep dive analysis and feature engineering for analytical models.
 
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 <ul>
 <li>
 3+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems.
 </li>
 <li>
 Masters degree in a quantitative field such as mathematics, statistics, computer science or engineering.
 </li>
 <li>
 Hands-on experiences with building marketing measurement solutions to quantify the business impact of marketing tactics and investments.
 </li>
 <li>
 Strong background in statistics and quantitative analysis, with experience in applying advanced statistical techniques to real-world problems.
 </li>
 <li>
 Expertise in at least one scripting language (ideally Python/R). Proficiency in SQL/Hive. Ability to write efficient SQL queries.
 </li>
 <li>
 Strong business and product sense. Strong skills in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
 </li>
 <li>
 Excellent communication skills, able to lead initiatives and communicate findings to the leadership and cross-functional teams. Explains work and thought processes clearly and concisely.
 </li>
 <li>
 Experience leading key technical projects.
 </li>
 <li>
 Strong Experimentation background.
 </li>
 <li>
 Statistical rigor. Experience with causal inference projects.
 
 
 
 </li>
 </ul>
 
 In-Office Requirement Statement
 
 
 
 <ul>
 <li>
 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.
 </li>
 <li>
 This role will need to be in the office for in-person collaboration 1-2 times/quarter and therefore can be situated anywhere in the country.
 
 
 
 </li>
 </ul>
 
 Relocation Statement:
 
 
 
 <ul>
 <li>
 This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.
 
 
 
 </li>
 </ul>
 At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.
 
 
 
 Information regarding the culture at Pinterest and benefits available for this position can be found here.
 
 
 
 US based applicants only
 
 
 $114,297&mdash;$235,319 USD
 
 
 
 Our Commitment To Inclusion
 
 
 
 Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you require a medical or religious accommodation during the job application process, please complete this form for support.
 
 
</div>

Data Scientist II, Growth Marketing

OpenAI

Careers
 
Data Scientist, People Innovation
 
Data Science - San Francisco
 
About the Role
 
We’re hiring a Data Scientist to support People Innovation Labs, a fast-moving engineering team embedded in the People organization focused on rethinking how we find and retain the best talent and empower everyone to do their best work.
 
From recruiting to culture, we’re designing systems and products that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation.
 
In this role, you’ll be embedded with Product and Engineering to ensure our work drives measurable business outcomes.
 
What You’ll Do
 
Define success metrics for agentic recruiting and HR systems, including leading indicators that enable weekly iteration.
 
Design measurement and experimentation frameworks for always-on systems across every stage of the candidate and employee lifecycle — using holdouts, staged rollouts, and quasi-experimental methods when needed.
 
Partner with PMs and engineers to instrument, evaluate, and monitor launches so every meaningful release has observability and a credible read on incremental value.
 
Translate behavioral and model-driven signals into decisions: what to scale, where to intervene, and how to allocate human and compute attention across segments.
 
Build repeatable decision loops (pre-launch criteria → post-launch read → next action) that convert analysis into shipped changes.
 
What We’re Looking For
 
10+ years in a quantitative role (e.g., Data Science, Decision Science), ideally at a product-led company or in the internal people software space.
 
Deep grounding in experimentation, causal inference, and applied statistics, with experience designing and interpreting tests in real-world, always-on environments.
 
Strong technical fluency in SQL and Python, including working directly with messy, incomplete behavioral data to quantify impact.
 
Proven track record of translating results into shipped decisions (product, lifecycle, targeting, routing).
 
Strong business judgment and a bias toward action: able to scope ambiguous problems, define success, and move quickly from insight to strategy.
 
Excellent communicator and partner to PMs/Engineers; comfortable influencing stakeholders and presenting recommendations to senior leadership.
 
Interest in building company culture and/or recruiting the world’s most talented people.
 
Nice to Have
 
Familiarity with large language models and AI-assisted operations platforms.
 
Experience working on operational automation and decision systems (routing, prioritization, optimization).
 
Experience operating in early-stage or rapidly evolving environments, including building measurement and experimentation frameworks from scratch.
 
About OpenAI
 
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
For additional information, please see
 
OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement
 
.
 
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through
 
this form
 
. No response will be provided to inquiries unrelated to job posting compliance.
 
We are committed to providing reasonable accommodations to applicants with disabilities.
 
OpenAI Global Applicant Privacy Policy
 
At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
Compensation
 
$230K – $342K + Offers Equity

Data Scientist, People Innovation

<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

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

Explore 197+ Applied scientist marketing measurement in San Francisco this March. Find roles across top companies and apply now to boost your career.