applied data scientist, evaluation & model behavior

data engineer

data engineer - finance Jobs in San Francisco

data engineer - finance

data scientist

ai training - research scientist (pst) Jobs in San Francisco

ai training - research scientist (pst)

applied data scientist, evaluation & model behavior Jobs in San Francisco

data scientist product

OpenAI

<div>
 
 About The Team
 
 
 
 Our Applied team brings OpenAI technologies to consumers and businesses around the world. We collaborate across research, engineering, design and business functions to turn cutting-edge AI advancements into impactful real-world applications. Our team has been behind notable product launches (ChatGPT, API, Sora), creating tools that help developers write code, enable businesses to operate more efficiently, and empower individuals to learn and create. As AI capabilities rapidly evolve, we focus on ensuring that our products are safe, accessible, and beneficial to all.
 
 
 
 About The Role
 
 
 
 As a Data Scientist on the Applied Product team, you will contribute to a data-driven product development culture for consumer and enterprise products at OpenAI. This is critical as our products reach millions of users and businesses worldwide. We are focused on aligning both research and product development to drive measurable impact for these individuals and organizations alike.
 
 
 You should expect to define our north-star metrics, design A/B tests, and establish source-of-truth dashboards that the entire company can use to answer their own product questions. Most importantly, you should expect to be a core member of the product development team.
 
 
 This role is based in San Francisco, CA or Seattle, WA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Embed with the product development team as a trusted partner, uncovering new ways to improve the product and drive growth
 </li>
 <li>
 Define and interpret A/B tests that help answer critical questions about the impact of model and UX changes to our product
 </li>
 <li>
 Establish a data-driven product development culture by defining, tracking, and operationalizing feature-, product-, and company-level metrics
 </li>
 <li>
 Develop and socialize dashboards, reports, and other ways of enabling the team and company to answer product data questions in a self-serve way
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You Have
 
 
 
 <ul>
 <li>
 5+ years experience in a quantitative role navigating highly ambiguous environments, ideally as an early data scientist or product analyst at a hyper-growth product company or research org
 </li>
 <li>
 Proposed, designed, and run rigorous experiments with clear insights and product recommendations utilizing SQL and Python
 </li>
 <li>
 Defined, implemented, and operationalized new feature and product-level metrics from scratch
 </li>
 <li>
 Excellent communication skills with demonstrated ability to communicate with product managers, engineers, and executives alike
 </li>
 <li>
 Strategic insights beyond the paradigm of statistical significance testing
 
 
 </li>
 </ul>
 
 You could be an especially great fit if you have:
 
 
 
 <ul>
 <li>
 Strong programming background, with ability to run simulations and prototype variants
 </li>
 <li>
 Experience validating quantitative insights with qualitative methods (e.g. surveys, UXR)
 </li>
 <li>
 Demonstrated prior experience in NLP, large language models, or generative AI
 
 
 </li>
 </ul>
 
 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&rsquo;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, and requests can be made via this link.
 
 
 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 Range: $230K - $385K
</div>

Data Scientist, Product

Medeloop

<div><h2 class="jobSectionHeader">The Role</h2>

This is a full-ownership data engineering role at the center of Medeloop's AI platform. You won't be maintaining pipelines someone else built, you'll be architecting the data backbone that powers AI agents doing real operations at scale. You'll work directly with data scientists, AI engineers, and product teams to turn raw, complex healthcare data into the clean, structured, semantically-rich foundation our AI scientists depend on. Your work shows up in customer products and research outcomes, not internal dashboards that no one reads.Candidates who currently perform these tasks exclusively through manual processes are unlikely to be suitable for this role. We require an individual who has already adopted and integrated AI techniques to enhance operational velocity, rather than one who is contemplating future experimentation.If you want to build something that genuinely changes how medical research gets done, this is the role.
<h2 class="jobSectionHeader">
What You'll Own</h2>
<ul><li>The healthcare data lake: curating, extending, and evolving it through new concepts, derived variables, and data models that directly inform our AI engines and customer products</li>
<li>AI-native data workflows: designing and operating AI-powered pipelines (using tools like Claude Code and agent frameworks) to automate harmonization, cleaning, quality checks, and summarization at scale</li>
<li>NLP and semantic infrastructure: building pipelines for entity extraction, concept normalization, embedding-based retrieval, and semantic search that power the AI Scientist platform</li>
<li>Novel data extraction approaches: experimenting with and building new methodologies for working with unstructured clinical data, not just applying existing playbooks</li>
<li>Research-grade data products: delivering analytical samples, cohorts, and final datasets that withstand scientific scrutiny and are actively used by researchers and customers</li>
<li>Data governance and observability protocols: including access controls, PHI/PII handling, data classification, compliance, monitoring, alerting, data freshness, and comprehensive documentation to enable self-service capabilities.</li>
</ul><h2 class="jobSectionHeader">What We're Looking For</h2>
<ul><li>3+ years of relevant data engineering or data management within an analytics-driven organization, with end-to-end ownership from raw ingestion to final data product</li>
<li>Deep hands-on experience with healthcare CDMs (OMOP, FHIR, PCORnet) &mdash; designing or extending them, not just querying</li>
<li>Knowledge of medical ontologies: UMLS, SNOMED CT, RxNorm</li>
<li>Experience with big data, data pipelines and tooling that support retrieval-augmented generation (RAG), vector integrations, embedding workflows, and other AI/ML workloads. Experience in big data tooling such as Spark, Iceberg, EMR</li>
<li>Fluent in Python and SQL; comfortable across structured and unstructured data</li>
<li>Proven NLP experience: semantic search, entity recognition, concept normalization, embedding pipelines</li>
<li>Strong grasp of inferential statistics and cohort methodology to be a real partner to data scientists and customers (as part of onboarding)</li>
<li>Experience contributing to an AI/ML product, especially in automated research or scientific discovery</li>
<li>Experience mentoring other engineers and providing technical leadership</li>
</ul><h2 class="jobSectionHeader">Bonus Points</h2>
<ul><li>Multi-cloud experience (AWS, Azure, GCP)</li>
<li>Authorship or contribution to peer-reviewed publications or technical reports</li>
</ul><h2 class="jobSectionHeader">Why Medeloop</h2>
<ul><li>Ownership from day one: small team, high-trust, no layers between your work and its impact</li>
<li>Technically ambitious: you'll build AI-powered workflows, not just support them</li>
<li>Real-world stakes: your work accelerates drug development, addresses health equity, and improves clinical research for institutions that matter</li>
<li>Strong foundation: Series A, top-tier investors, and a data asset (200M+ patient records) that most companies spend years trying to build</li></ul></div>

Senior AI Data Engineer– Agentic Healthcare Platform

AGI, Inc.

<div><h1 class="jobSectionHeader">Think Different. Build the Future.
</h1><h2 class="jobSectionHeader">Our Mission</h2>
Build everyday AGI. Trustworthy, consumer-grade agents that redefine human&ndash;AI collaboration for millions. Software shouldn&rsquo;t wait for commands; it should partner with you, amplifying what you can do every single day.<h2 class="jobSectionHeader">
Why AGI, Inc.</h2>
We&rsquo;re a stealth team of elite founders and AI researchers, with backgrounds spanning Stanford, OpenAI, and DeepMind. We&rsquo;re industry leaders in mobile and computer-use agents, bringing these capabilities to consumer scale.
Grounded in years of agent research, our AI is designed with trustworthiness and reliability as core pillars, not afterthoughts.
We are supported by tier-1 investors who funded the first generation of AI giants; now they&rsquo;re backing us to build the next: everyday AGI. (Watch the demo)
If you see possibility where others see limits, read on.<h2 class="jobSectionHeader">
About the Role</h2>
As an Applied Scientist focused on Evaluation &amp; Model Behavior, you will design and implement the systems used to measure and improve the performance of Computer Use Agents.
This is not a support role. You will be responsible for the technical definition of model quality, including the design of evaluation metrics, the curation of training datasets, and the engineering of system prompts. You'll work directly with the engineering team to translate product requirements into technical specifications and quantifiable benchmarks.
You'll focus on rigor, clarity, and impact, ensuring every metric, dataset, and prompt moves us toward more reliable, trustworthy agents.<h2 class="jobSectionHeader">
What You'll Do</h2>
Model Behavior Design: Translate product requirements into technical specifications for model behavior. Engineer system prompts and few-shot examples to address specific capability gaps and behavioral failures.
Evaluation Design: Define metrics for reasoning, tool usage, and safety, and validate these metrics against human judgment to ensure statistical rigor.
Data Strategy: Design algorithms to filter, score, and select training data. Write Python scripts to sanitize inputs and manage the training data lifecycle from raw logs to high-quality datasets.
Failure Analysis: Investigate regressions in model benchmarks. Diagnose root causes, distinguishing between data quality issues, prompt instruction failures, or underlying model capability gaps and implement fixes.
Ground Truth Management: Define rubrics and guidelines for human annotation. Maintain reference datasets (&quot;Golden Sets&quot;) to establish a consistent baseline for model performance evaluation.<h2 class="jobSectionHeader">
Minimum Qualifications</h2><ul><li>
Master's degree or PhD in Computer Science, Data Science, Statistics, or a related technical field, or equivalent practical experience</li><li>
3+ years of experience in Data Science, Machine Learning, or Applied Science</li><li>
Proficiency in Python, with experience writing production-quality code for data pipelines or evaluation harnesses</li><li>
Experience with experimental design, A/B testing, or statistical analysis</li></ul><h2 class="jobSectionHeader">
Preferred Qualifications</h2><ul><li>
Experience with Large Language Models (LLMs), including prompt engineering, fine-tuning, or RLHF workflows</li><li>
Experience building automated evaluation systems or implementing model-based evaluation frameworks</li><li>
Ability to translate product requirements into measurable technical metrics</li><li>
Experience managing human-in-the-loop data pipelines or annotation quality control</li></ul><h2 class="jobSectionHeader">
Why This Role Matters</h2>
You can't improve what you can't measure. You can't ship what you can't trust.
You will define the technical definition of quality for our agents &mdash; the metrics that predict real-world success, the datasets that encode user intent, and the prompts that shape model behavior. Your work will directly determine how quickly we can iterate and how confidently we can ship.<h2 class="jobSectionHeader">
Our Culture</h2>
All in, in person &mdash; work moves faster face-to-face
 
Ship by default &mdash; speed and polish can coexist
 
One band, one sound &mdash; radical candor, zero politics<h2 class="jobSectionHeader">
Perks</h2>
Competitive company-sponsored medical, dental, and vision insurance
 
Top-tier relocation and immigration support<h2 class="jobSectionHeader">
How to Apply</h2>
Send us:<ul><li>
A link &mdash; or 60-second video &mdash; of something you built and why it matters</li><li>
Your resume or LinkedIn</li><li>
Two sentences on the hardest problem you've cracked</li></ul>
Every exceptional candidate hears back within 48 hours.
If you see possibility where others see limits, we'd love to meet you.</div>

Applied Data Scientist, Evaluation & Model Behavior

Lyft

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

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

As a Data Scientist on the Risk Solutions team, you will drive a mission critical to both the safety of our community and the financial resilience of our platform. You'll partner cross-functionally with Product, Engineering, Actuarial and Claims teams to transform complex data into actionable strategies. You will serve as an analytical lead for claims and road safety initiatives, designing experiments and predictive models aimed at reducing accident frequency and claim severity to optimize long-term risk outcomes. If you are a problem-solver eager to apply high-level data science to real-world safety and financial challenges, this role offers a direct path to high-impact innovation.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul><li>Leverage large-scale data and analytic frameworks to identify high-impact opportunities to reduce the total cost of claims.</li>
<li>Partner with product managers, engineers, actuaries, claims, and operators to translate data insights into decisions and action</li>
<li>Construct and fit statistical, machine learning, or optimization models</li>
<li>Design and analyze online experiments; communicate results and act on launch decisions</li>
<li>Develop analytical frameworks to monitor business and product performance</li>
<li>Establish metrics that measure the health of our products, the business, as well as the driver experience</li>
<li>Collaborate with the Claims team to identify high-impact opportunities where data-driven interventions can reduce the total cost of claims.</li>
</ul><h2 class="jobSectionHeader">Experience:</h2>
<ul><li>Degree in a quantitative field such as statistics, actuarial science, economics, applied math, operations research or engineering (advanced degrees preferred), or relevant work experience</li>
<li>5+ years of industry experience in a data science, analytics, or management consulting role.
</li><li>End-to-end experience with data, including querying, aggregation, analysis, and visualization</li>
<li>Ability to manage, influence, negotiate, and inspire others in a fast-moving environment</li>
<li>Proficiency in SQL and Python</li>
<li>Experience with insurance claims analytics a plus</li>
<li>Strong oral and written communication skills, and ability to collaborate with cross-functional partners</li></ul> 

<h2 class="jobSectionHeader">
Benefits: 
</h2>
<ul><li>Great medical, dental, and vision insurance options with additional programs available when enrolled</li>
<li>Mental health benefits</li>
<li>Family building benefits</li>
<li>Child care and pet benefits</li>
<li>401(k) plan with company match to help save for your future</li>
<li>In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off</li>
<li>18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible</li>
<li>Subsidized commuter benefits</li>
<li>Monthly Lyft credits and complimentary Lyft Pink membership</li>
</ul>
Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.

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

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

Senior Data Scientist, Decisions - Risk

<div>
 
 About The Team
 
 
 
 Our B2B product organization is building the systems that will accelerate and automate how companies operate using AI coworkers.Our vision is to enable companies to scale to $1B+ with teams of fewer than five people by leveraging AI agents and automation. We are building the infrastructure, products, and analytics that allow organizations to deploy fleets of AI agents, automate workflows, and dramatically increase employee productivity. This team sits at the center of the future of work: defining how humans collaborate with AI systems across companies, workflows, and knowledge.
 
 
 
 About The Role
 
 
 
 We are looking for a product-focused Data Scientist to help shape the next generation of AI-powered enterprise products, including ChatGPT Enterprise and agentic automation systems.
 
 
 This is not a traditional analytics role. You will work directly with product managers, engineers, and researchers to define how AI agents behave, how organizations adopt them, and how we measure their impact on work.
 
 
 You&rsquo;ll analyze how users interact with AI systems, inform product strategy, and help build the measurement frameworks that guide the future of enterprise AI.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Partner closely with product, engineering, and research teams to shape AI-powered enterprise products
 </li>
 <li>
 Define metrics and measurement frameworks for AI agents, automation workflows, and enterprise adoption
 </li>
 <li>
 Analyze how organizations use AI tools and identify opportunities to improve product experience and business impact
 </li>
 <li>
 Drive insights around enterprise adoption, retention, and value realization
 </li>
 <li>
 Inform product decisions around agent orchestration, enterprise workflows, and AI productivity tools
 </li>
 <li>
 Design experiments and evaluations that improve AI system performance and user outcomes
 </li>
 <li>
 Help define how companies operate with AI coworkers and automated workflows
 
 
 </li>
 </ul>
 
 What We&rsquo;re Looking For
 
 
 
 
 Must Have:
 
 
 
 <ul>
 <li>
 Strong product analytics or data science experience
 </li>
 <li>
 Deep curiosity about AI systems and how they change how work gets done
 </li>
 <li>
 Ability to work closely with product and engineering teams in 0&rarr;1 product environments
 </li>
 <li>
 Strong analytical skills (experimentation, behavioral analysis, product metrics)
 </li>
 <li>
 Builder mindset &mdash; someone who wants to shape products, not just analyze them
 
 
 </li>
 </ul>
 
 Nice To Have
 
 
 
 <ul>
 <li>
 Experience with B2B SaaS or enterprise analytics
 </li>
 <li>
 Experience with developer platforms, APIs, or technical products
 </li>
 <li>
 Background in AI/ML systems, agent frameworks, or LLM-based products
 </li>
 <li>
 Systems thinking around how complex tools and workflows operate at scale
 
 
 </li>
 </ul>
 
 Who Thrives Here
 
 
 
 <ul>
 <li>
 AI-native &mdash; actively experimenting with and building with AI tools
 </li>
 <li>
 Product thinkers who want to shape the future of work
 </li>
 <li>
 Builders who enjoy early-stage ambiguity and 0&rarr;1 problems
 </li>
 <li>
 Operators who can work independently and drive large parts of a product area
 
 
 </li>
 </ul>
 
 Impact
 
 
 
 
 You Will Help Define
 
 
 
 <ul>
 <li>
 How organizations deploy and manage AI agents
 </li>
 <li>
 How AI transforms enterprise productivity
 </li>
 <li>
 The measurement systems behind AI-native companies
 </li>
 <li>
 This is an opportunity to help create the &ldquo;Codex moment&rdquo; for non-coding work &mdash; defining how businesses operate in an AI-first world.
 
 
 </li>
 </ul>
 
 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&rsquo;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, and requests can be made via this link.
 
 
 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 Range: $293K - $515K
</div>

Data Scientist, B2B

Prolific

<div>
 
 AI Trainer &ndash; Research Scientists
 
 
 
 
 
 About Prolific
 
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 
 The role
 
 
 
 
 We&rsquo;re looking for people with Research Scientist experience to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world&rsquo;s biggest AI labs. If you have the necessary experience, we&rsquo;ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a Domain Expert participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to $50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
 
 
 
 
 What you&rsquo;ll be doing in the role
 
 
 
 
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 
 
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
 
 
 Improving cutting-edge AI models using your experience in research and experimentation
 
 
 
 
 What you&rsquo;ll bring
 
 
 
 
 Experience working as a Research Scientist or in a closely related research role
 
 
 A strong understanding of scientific methodology, experimental design, and data analysis
 
 
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 
 
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 
 
 A reliable and fast internet connection and access to a computer
 
 
 A Paypal account to receive payment from our clients*
 
 
 
 
 Why Prolific is a great platform to join as a Domain Expert participant
 
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 
 
 <ul>
 <li>
 Participants are self-employed and need to declare earnings to their respective tax authorities. Prolific has no liability for any tax obligations or reporting requirements resulting from compensation received through this platform. Each participant is solely responsible for compliance with applicable tax laws in their jurisdiction.
 
 
 </li>
 </ul>
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
</div>

AI Training - Research Scientist (PST)

Triumph

<div><h1 class="jobSectionHeader">About Us</h1>
Triumph makes mobile gaming more thrilling by letting players wager - and win - real money, play in mass multiplayer games, and compete in social tournaments. We've built the top app in our App Store category and sustained exponential month-over-month growth on our revenue and active players. We're hyper-scaling our team and continuing to innovate, launching new products like Rips, our collectibles app, which has found huge success and is continuing to expand. And we're just getting started.
Triumph is backed by some of the top consumer VCs including Goodwater Capital, General Catalyst, and DraftKings Drive Fund.<h1 class="jobSectionHeader">
The Role</h1>
As a Data Scientist, you'll own the quantitative systems that drive how millions of real-money players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.
You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches real money and real users. You see the impact in the numbers the next day.<h1 class="jobSectionHeader">
What You'll Do</h1><ul><li>
Monetization &amp; Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.</li><li>
User Journey &amp; Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.</li><li>
Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.</li><li>
Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.</li><li>
Growth &amp; Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.</li><li>
Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.</li><li>
True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.</li><li>
Proficiency in Python and SQL.</li><li>
Experience working with large-scale user or behavioral datasets.</li></ul><h1 class="jobSectionHeader">
Preferred Qualifications</h1><ul><li>
Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.</li><li>
Prior experience as a quantitative trader or quantitative researcher.</li><li>
Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.</li><li>
Nationally competitive in any activity. Some members of our team include national champions in debate, Clash Royale, and Poker.</li></ul><h1 class="jobSectionHeader">
Why Triumph?</h1><ul><li>
High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.</li><li>
High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.</li><li>
High energy. Passionate team who are proud of our work and velocity (16x year over year growth).</li><li>
Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.</li></ul>
Our team gathers 5 days a week at Triumph&rsquo;s headquarters at Levi&rsquo;s Plaza in San Francisco.
Compensation Range: $160K - $265K</div>

Data Scientist

Explore 321+ Data scientist product in San Francisco this April. Find roles across top companies and apply now to boost your career.