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Data Scientist, Product Analytics

Whatnot

<div>
 
 
 🚀 Join the Future of Commerce with Whatnot!
 
 
 
 
 Whatnot is the largest livestream shopping platform in North America and Europe to buy, sell, and discover the things you love. Whether it's trading cards, fashion, electronics, or live plants, our sellers are building real businesses across hundreds of categories. We're building live commerce at a scale that's never been done in the West, and there's no playbook to copy. The people here are shaping how an entirely new industry develops.
 
 
 As a remote co-located team, we're inspired by our values and anchored in hubs across the US, UK, Ireland, Poland, Germany, and Australia. We move fast, stay close to our users, and focus on the work that drives the most impact.
 
 
 We're one of the fastest growing marketplaces and were recently named the #1 Best Startup Employer in America by Forbes. Check out the latest Whatnot updates on our news and engineering blogs and join us as we enable anyone to turn their passion into a business and bring people together through commerce.
 
 
 
 💻 Role
 
 
 
 As Whatnot rapidly scales, data is central to shaping our product strategy and helping us build delightful, high-performing experiences for both buyers and sellers. We&rsquo;re looking for a
 
 Product Data Scientist
 
 who will partner closely with Product, Engineering, Design, and Operations to drive insights, experimentation, and decision-making across the company.
 
 
 
 In This Role, You Will
 
 
 
 
 🔍 Generate Insights &amp; Shape Product Direction
 
 
 
 <ul>
 <li>
 Define and own the KPIs that measure product health, user engagement, and marketplace performance.
 </li>
 <li>
 Analyze user behavior, product usage patterns, and marketplace dynamics to identify opportunities and inform product priorities.
 </li>
 <li>
 Translate complex data into actionable recommendations for product and leadership teams.
 
 
 </li>
 </ul>
 
 🧪 Drive Experimentation &amp; Measurement
 
 
 
 <ul>
 <li>
 Partner with product managers and engineers to design, implement, and evaluate A/B tests and feature rollouts.
 </li>
 <li>
 Develop frameworks for causal inference, impact measurement, and long-term product evaluation.
 </li>
 <li>
 Build scalable methodologies to understand feature performance and guide iteration.
 
 
 </li>
 </ul>
 
 🛠 Build Data Products &amp; Tools
 
 
 
 <ul>
 <li>
 Use our modern data stack to build dashboards, data pipelines, and self-serve tools that empower teams across Whatnot.
 </li>
 <li>
 Partner with engineers to improve data accessibility, ensure data quality, and support instrumentation for new product features.
 
 
 </li>
 </ul>
 
 🤝 Lead Cross-Functional Collaboration
 
 
 
 <ul>
 <li>
 Advocate for data-driven decision-making and foster a culture of measurement across the product organization.
 </li>
 <li>
 Communicate insights clearly to both technical and non-technical audiences, influencing roadmaps and strategic decisions.
 </li>
 <li>
 Serve as a thought partner to product leads, shaping how we build, launch, and iterate on experiences across the platform.
 
 
 </li>
 </ul>
 
 US Based
 
 
 
 
 We offer flexibility to work from home or from one of our global office hubs, and we value in-person time for planning, problem-solving, and connection. Team members in this role must live within commuting distance of our New York, Seattle, Los Angeles, and San Francisco hubs.
 
 
 
 
 👋 You
 
 
 
 People who do well at Whatnot tend to be comfortable figuring things out as they go, biased toward action, and genuinely curious about what they're building. They care more about outcomes than credit and stay close to the product and the people using it.
 
 
 
 🎓 Experience &amp; Expertise
 
 
 
 As our next
 
 Product Data Scientist
 
 , you bring:
 
 
 <ul>
 <li>
 3+ years of experience in Data Science, Decision Science, or Analytics within a product-focused organization.
 </li>
 <li>
 A bachelor&rsquo;s degree in Computer Science, Economics, Statistics, or a related quantitative field or equivalent experience.
 </li>
 <li>
 Proven experience applying statistical and analytical methods to real-world product problems.
 
 
 </li>
 </ul>
 
 🧠 Technical Skills
 
 
 
 <ul>
 <li>
 Advanced SQL skills and experience with modern data warehouses (Snowflake, BigQuery, Redshift) and tools like Spark or DBT.
 </li>
 <li>
 Proficiency with Python or R for data analysis, modeling, and experimentation.
 </li>
 <li>
 Experience designing and analyzing A/B tests and understanding causal inference techniques.
 </li>
 <li>
 Strong data visualization skills and familiarity with BI tools for building interactive dashboards.
 
 
 </li>
 </ul>
 
 🗣 Collaboration &amp; Leadership
 
 
 
 <ul>
 <li>
 Ability to communicate complex ideas clearly, concisely, and impactfully across diverse stakeholders.
 </li>
 <li>
 Experience leading cross-functional projects and influencing product strategy with data.
 </li>
 <li>
 Comfortable working in fast-paced, ambiguous environments with a high degree of ownership.
 
 
 </li>
 </ul>
 
 💰Compensation
 
 
 
 
 For Full-Time (Salary) US based applicants:
 
 $185,000/year to $240,000/year + benefits + equity.
 
 
 The salary range may be inclusive of several levels that would be applicable to the position. Final salary will be based on a number of factors including, level, relevant prior experience, skills, and expertise. This range is only inclusive of base salary, not benefits (more details below) or equity.
 
 
 
 🎁 Benefits
 
 
 
 <ul>
 <li>
 Flexible Time off Policy and Company-wide Holidays (including a spring and winter break)
 </li>
 <li>
 Health Insurance options including Medical, Dental, Vision
 </li>
 <li>
 Work From Home Support
 </li>
 <ul>
 <li>
 Home office setup allowance
 </li>
 <li>
 Monthly allowance for cell phone and internet
 </li>
 </ul>
 <li>
 Care benefits
 </li>
 <ul>
 <li>
 Monthly allowance for wellness
 </li>
 <li>
 Annual allowance towards Childcare
 </li>
 <li>
 Lifetime benefit for family planning, such as adoption or fertility expenses
 </li>
 </ul>
 <li>
 Retirement; 401k offering for Traditional and Roth accounts in the US (employer match up to 4% of base salary) and Pension plans internationally
 </li>
 <li>
 Monthly allowance to dogfood the app
 </li>
 <ul>
 <li>
 All Whatnauts are expected to develop a deep understanding of our product. We're passionate about building the best user experience, and all employees are expected to use Whatnot as both a buyer and a seller as part of their job (our dogfooding budget makes this fun and easy!).
 </li>
 </ul>
 <li>
 Parental Leave
 </li>
 <ul>
 <li>
 16 weeks of paid parental leave + one month gradual return to work *company leave allowances run concurrently with country leave requirements which take precedence.
 </li>
 </ul>
 </ul>
 
 
 💛 EOE
 
 
 
 
 Whatnot is proud to be an Equal Opportunity Employer. We value diversity, and we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, parental status, disability status, or any other status protected by local law. We believe that our work is better and our company culture is improved when we encourage, support, and respect the different skills and experiences represented within our workforce.
 
 
 Compensation Range: $185K - $240K
 
 
</div>

Andiamo

<div>
 Data Scientist &ndash; Product &amp; AI
 
 
 
 About The Role
 
 
 
 We are looking for a
 
 Data Scientist
 
 to help solve complex, high-impact problems in product development and AI. You will work with
 
 large-scale, high-dimensional data sets
 
 , applying statistical methods, machine learning, and experimentation to guide product decisions and improve user experiences. Your insights will influence the direction of features, platforms, and strategies used by thousands of organizations.
 
 
 As a mid-level data scientist, you&rsquo;ll own projects end-to-end: defining success metrics, designing experiments, building predictive models, and communicating findings to cross-functional partners. You&rsquo;ll collaborate with product managers, engineers, and designers to turn raw data into actionable insights that drive measurable business and product outcomes.
 
 
 This role is a chance to move beyond dashboards&mdash;you&rsquo;ll uncover patterns, tell compelling stories with data, and contribute to building scalable data science practices that push the boundaries of what&rsquo;s possible.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Apply Analytical Methods: Use statistical modeling, machine learning, and data visualization to extract insights and guide product strategy.
 </li>
 <li>
 Experiment &amp; Learn: Design, run, and analyze A/B tests and other experiments to evaluate product changes and quantify impact.
 </li>
 <li>
 Build Predictive Models: Develop models that forecast user behavior, product performance, and key metrics.
 </li>
 <li>
 Define Success Metrics: Establish clear goals and KPIs that align product teams around measurable outcomes.
 </li>
 <li>
 Collaborate Across Teams: Partner with engineers, designers, and product leaders to ensure insights are translated into impactful features.
 </li>
 <li>
 Communicate Findings: Present results and recommendations to stakeholders, framing technical insights in clear, actionable terms.
 </li>
 <li>
 Contribute to Data Platforms: Work with engineering partners to improve data pipelines, instrumentation, and experimentation frameworks.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 Professional Experience: Around 5 years of applied data science experience in product analytics, business intelligence, or machine learning.
 </li>
 <li>
 Programming Skills: Proficiency in SQL and Python (or R) for data manipulation, modeling, and analysis.
 </li>
 <li>
 Experimentation: Familiarity with experimental design, causal inference, and A/B testing at scale.
 </li>
 <li>
 Statistical Foundation: Strong grounding in probability, statistics, and data-driven problem solving.
 </li>
 <li>
 Communication: Ability to clearly present technical analyses to non-technical audiences and drive alignment on decisions.
 </li>
 <li>
 Education: Bachelor&rsquo;s degree in Statistics, Mathematics, Computer Science, Engineering, or related field; Master&rsquo;s degree a plus.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience working with product teams or SaaS platforms.
 </li>
 <li>
 Knowledge of ML frameworks (scikit-learn, TensorFlow, or PyTorch) and data visualization tools (Tableau, Looker, or similar).
 </li>
 <li>
 Exposure to cloud data environments (AWS, GCP, or Azure).
 
 
 </li>
 </ul>
 ✨
 
 Why Join
 
 : This is your chance to tackle challenging data problems in AI and product development. You&rsquo;ll apply advanced methods, work with talented colleagues, and contribute to products that affect millions of users and billions of data points&mdash;all while growing your skills and career.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Global Tech Leader

Apple

Apple is where individual imaginations gather together, committing to the values that lead to great work. Every new product we build, service we create, or Apple Store experience we deliver is the result of us making each other's ideas stronger. That happens because every one of us shares a belief that we can make something wonderful and share it with the world, changing lives for the better. It's the diversity of our people and their thinking that inspires the innovation that runs through everything we do. When we bring everybody in, we can do the best work of our lives. Here, you'll do more than join something - you'll add something. 
 
Description 
 
The Siri Quality Engineering team is seeking an Analytics Data Scientist to build a Curated, Accurate, Reliable data lake-a governed lakehouse with point-in-time and near-real-time pipelines, and a clear semantic layer-so teams trust and use data. You will ultimately be part of a collaborative team that's responsible for understanding how well our products work, advocating for critical changes, and representing how they'll be experienced by our customers. We deliver descriptive, diagnostic, prescriptive, and predictive analytics that show what&rsquo;s happening, explain why, recommend what to do, and empower decision automation. We publish certified metrics and models used in executive-facing reports, raising product quality, speeding releases, and reducing risk across all Apple platforms and locales. As a member of our passionate group in Siri, you will have the unique and rewarding opportunity to shape and improve our products to delight and inspire millions of Apple's customers every day.&quot;,&quot;responsibilities&quot;:&quot;Turning data into decisions. Lead analytics across four modes-Descriptive, Diagnostic, Prescriptive, Predictive-to improve engineering efficiency and product quality. 
 
Define KPIs and metrics; automate exec-ready reporting and anomaly detection. 
 
Explain drivers with deep dives, causal/correlation analysis, and cohorting. 
 
Recommend actions using optimization, simulations, and experiment results. 
 
Build and productionize models (forecasting, classification, risk/quality scoring). 
 
Translate insight to action with clear narratives, dashboards, and decision rules. 
 
Standardize definitions (data dictionary, glossary); surface and drive data-quality fixes with partners. 
 
Run A/B tests; design guardrails; monitor impact. 
 
Preferred Qualifications 
 
Forecasting/time-series; optimization (LP/MIP) or simulation. 
 
MLOps basics (versioning, evaluation, monitoring). 
 
Tableau or similar for self-service analytics. 
 
Web Developer experience is a plus. 
 
BS/MS in a quantitative field. 
 
Minimum Qualifications 
 
5+ years in product/ops analytics or data science. 
 
Expert SQL; strong Python (pandas, NumPy, scikit-learn or PySpark). 
 
Statistics and experiment design (hypothesis testing, power, basic causal inference). 
 
Proven record of turning analysis and models into shipped decisions with measurable impact. 
 
Excellent communication with both technical and executive audiences. 
 
Experience with agentic AI-assisted coding. 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $141,800 and $258,600, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Analytics Data Scientist - Quality Engineering, Siri

OpenAI

<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

Cribl

<div><div>Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what's next.

We're one of the fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we're remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.</div>
Why You'll Love This Role

Cribl is hiring a Senior Data Scientist to join and grow our internal data science practice. In this role, you'll use predictive models and advanced analytics to give stakeholders clear foresight into what's likely to happen and what to do next. This role is embedded in our centralized data organization, reporting to our Staff Data Scientist, partnering closely with teams like Finance, GTM, and People. You'll turn rich data sets into forward-looking insights that guide planning, business strategy, and execution, and you'll contribute to the technical standards and culture that make our &quot;Foresight First&quot; vision a reality.

We pride ourselves on fostering a collaborative and innovative culture where team members enjoy working together - whether remotely or over a meal at a foodie hot spot. If you're someone who thrives in an entrepreneurial environment and is eager to contribute to a company poised for legendary success in the tech industry, we want to hear from you! 

As An Active Member Of Our Team, You Will&hellip;
<ul>
<li>Own end-to-end data science initiatives that translate ambiguous business questions into clear analytical and modeling problems, from scoping through implementation.</li>
<li>Build, operationalize, and continuously improve machine learning models in partnership with Data Engineering to ensure scalable training &amp; evaluation workflows in production.</li>
<li>Evaluate and interpret the performance of ML models (e.g., classification, recommendation), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions.</li>
<li>Conduct deep-dive analyses using advanced statistical methods to surface actionable insights to stakeholders and positively influence org-wide decision quality.</li>
<li>Apply statistical modeling, experimentation, and AI-assisted analytics to expand how Cribl uses data to answer challenging questions.</li>
<li>Communicate findings clearly and persuasively to executives and cross-functional stakeholders to influence strategic decision-making.</li>
<li>Contribute to technical best practices and team standards, and provide mentorship to junior team members as the practice grows.</li>
<li>Partner closely with Data Engineering, Analytics, and Governance to define data requirements, improve data quality, and ensure the team can efficiently generate trustworthy insights.</li>
<li>We are a remote-first company and work happens across many time-zones &ndash; you may be required to occasionally perform duties outside your standard working hours.</li></ul> 
 
If You've Got It - We Want It
<ul>
<li>5+ years of experience in data science or applied statistics with a track record of driving data science projects with meaningful business impact at a software company.</li>
<li>Strong background in experiment design, causal inference, predictive modeling, and ability to distinguish signal vs noise.</li>
<li>Advanced SQL and Python skills, with experience working on large, messy, multi-source datasets within a modern data stack such as cloud data warehouses and transformation frameworks.</li>
<li>Proven ownership of end-to-end data science and ML solutions, from problem framing and data preparation through modeling, validation, deployment to production in partnership with Data Engineering, and ongoing monitoring.</li>
<li>Ability to work effectively in ambiguous, fast-changing environments, navigating from problem framing through implementation and iteration.</li>
<li>Excellent communication, including the ability to present complex findings to non-technical audiences and contribute to strategic decisions</li>
<li>Familiarity with AI-assisted workflows, including leveraging LLMs as tools to accelerate analysis, surface insights, or augment modeling work.</li></ul> 
 
Salary Range ($120,000 - $175,000)

The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate's job-related knowledge, skills, and experience. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus. 
 
#LI-JB1 
#LI-Remote<div>
Bring Your Whole Self 
 
Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We're building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.

Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you'll ever meet at cribl.io/about-us.</div></div>

Senior Data Scientist

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied Scientist

Explore 401+ Data scientist product analytics in San Francisco this May. Find roles across top companies and apply now to boost your career.

401 data scientist product analytics jobs In San Francisco

Data Scientist, Product Analytics

Data Scientist, Product Analytics

Data Scientist - Global Tech Leader

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