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data scientist finance forecastingnew

Anthropic

<div><div><h2 class="jobSectionHeader">About Anthropic</h2>

Anthropic&rsquo;s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</div><div><h2 class="jobSectionHeader">
About the role</h2>

As an early member of our Finance Analytics and Business Intelligence team, you will play an instrumental role in our company's mission of building safe and beneficial artificial intelligence by establishing robust analytics engineering and business intelligence capabilities for our Finance &amp; Accounting organization. In this unique company, technology, and moment in history, your work will be critical to ensuring accurate financial reporting, streamlining accounting processes, and supporting our financial operations as we deploy safe, frontier AI at scale to the world.

As a founding Data Scientist on Anthropic's Finance Forecasting team, you'll own revenue forecasting models that drive capacity planning and board reporting, build the backtesting and accuracy discipline that makes those forecasts trustworthy, and lead causal measurement work that tells us how much a given launch or event actually moved revenue &mdash; turning what is currently a best-guess conversation into a designed, repeatable readout.

We're hiring for two seats on this team, and we expect candidates to lead with depth in either production time-series forecasting or causal inference. Both shapes are first-class; tell us in your application which one feels more like you.

This is a build role on a small team. The forecast is visible inside the company, and when it's wrong, people notice. We're looking for someone who would rather have their models scored than stay vague, and who is excited to set the bar for how forecasting is done here.
<h2 class="jobSectionHeader">
Responsibilities:</h2>
<ul>
<li>Own a core piece of the team's modeling work &mdash; either the production revenue forecasts themselves (scoping, development, backtesting, deployment, monitoring) or the causal measurement program for launches and events
</li>
<li>Build and run backtesting and accuracy tracking for your models, and use the results to improve quality cycle over cycle
</li>
<li>Contribute to the team's broader research direction, including event-aware forecast architectures, hierarchical reconciliation, and causal designs that hold up under launch-driven step-changes
</li>
<li>Translate model output and accuracy results into clear recommendations for Finance and executive leadership
</li>
<li>Partner with the team's Analytics Engineer on feature pipelines, model deployment, and the forecast store
</li>
</ul><h2 class="jobSectionHeader">You may be a good fit if you:</h2>
<ul>
<li>Have substantial experience in data science, forecasting, or quantitative finance, including time owning models in production rather than only in notebooks
</li>
<li>Are deeply fluent in Python and SQL and comfortable productionizing what you build
</li>
<li>Have a strong applied statistics foundation, with depth in either production time-series methods (Prophet, ETS, ARIMA, gradient-boosted approaches, neural forecasting, hierarchical reconciliation) or causal inference (difference-in-differences, synthetic control, Bayesian structural time series, event studies)
</li>
<li>Have built backtesting and accuracy-tracking discipline before and are comfortable having your models scored publicly
</li>
<li>Have presented and defended a forecast or causal estimate to executives
</li>
<li>Have a bias for action and do your best work in ambiguous, early-stage environments
</li>
</ul><h2 class="jobSectionHeader">Strong candidates may also have:</h2>
<ul>
<li>Experience with exogenous-regressor or event-aware forecasting approaches
</li>
<li>Familiarity with hybrid or foundation-model forecasting (TimeGPT-class systems)
</li>
<li>Background in pricing and elasticity modeling or marketing-mix modeling
</li>
<li>Experience forecasting a consumption-based or usage-billed business (cloud, API, marketplace)
</li>
</ul><h2 class="jobSectionHeader">What success looks like in your first year:</h2>
<ul>
<li>A cross-methodology accuracy baseline is published as a standing Finance metric
</li>
<li>The base revenue forecast is measurably more accurate than today's consensus on the same out-of-sample window
</li>
<li>Launch incrementality is a standing readout with a designed, backtested method behind it
</li>
<li>Forecasts are queryable from the forecast store and feeding capacity planning and board reporting
</li>
</ul><h2 class="jobSectionHeader">Things to know</h2>

Anthropic's business is growing quickly, with launch-driven step-changes that mean what worked last quarter may not generalize. Methodology direction is a research program, not a settled architecture. You'll be building practices and systems while also delivering a monthly number, alongside an Analytics Engineer who is building the platform underneath you.</div><div><div><div><div>
The annual compensation range for this role is listed below.

For sales roles, the range provided is the role&rsquo;s On Target Earnings (&quot;OTE&quot;) range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.</div></div><div>
Annual Salary:</div><div>
$270,000 - $320,000 USD</div></div></div><div><h2 class="jobSectionHeader">
Logistics</h2>

Minimum education: Bachelor&rsquo;s degree or an equivalent combination of education, training, and/or experience

Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience

Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position

Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.

Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team. 
 
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links&mdash;visit anthropic.com/careers directly for confirmed position openings.
<h2 class="jobSectionHeader">
How we're different</h2>

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact &mdash; advancing our long-term goals of steerable, trustworthy AI &mdash; rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI &amp; Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
<h2 class="jobSectionHeader">
Come work with us!</h2>

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process</div></div>

Data Scientist, Finance ForecastingNew

Twitch

<div>
 
 About Us
 
 
 
 Twitch is the world&rsquo;s biggest live streaming service, with global communities built around gaming, entertainment, music, sports, cooking, and more. It is where thousands of communities come together for whatever, every day.
 
 
 We&rsquo;re about community, inside and out. You&rsquo;ll find coworkers who are eager to team up, collaborate, and smash (or elegantly solve) problems together. We&rsquo;re on a quest to empower live communities, so if this sounds good to you, see what we&rsquo;re up to on LinkedIn and X, and discover the projects we&rsquo;re solving on our Blog. Be sure to explore our Interviewing Guide to learn how to ace our interview process.
 
 
 
 About The Role
 
 
 
 We are looking for an experienced Data Scientist to support our central analytics and finance disciplines at Twitch. Bringing to bear a mixture of data analysis, dashboarding, and SQL query skills, you will use data-driven methods to answer business questions, and deliver insights that deepen understanding of our viewer behavior and monetization performance. Reporting to the VP of Finance, Analytics, and Business Operations, your team will be located in San Francisco.
 
 
 Our team is based in San Francisco, CA.
 
 
 
 You Will:
 
 
 
 
 <ul>
 <li>
 Create actionable insights from data related to Twitch viewers, creators, advertising revenue, commerce revenue, and content deals.
 </li>
 <li>
 Develop dashboards and visualizations to communicate points of view that inform business decision-making.
 </li>
 <li>
 Create and maintain complex queries and data pipelines for ad-hoc analyses.
 </li>
 <li>
 Author narratives and documentation that support conclusions.
 </li>
 <li>
 Collaborate effectively with business partners, product managers, and data team members to align data science efforts with strategic goals.
 
 
 
 </li>
 </ul>
 
 You Have:
 
 
 
 
 <ul>
 <li>
 3+ years of data science experience with a Bachelor's degree in a quantitative field (e.g., Statistics, Business Analytics, Data Science, Mathematics, Economics, Engineering or Computer Science).
 </li>
 <li>
 Expertise in using SQL for data analysis, reporting, and dashboarding.
 </li>
 <li>
 Expertise with visualization tools like Tableau or Quicksight.
 </li>
 <li>
 Experience with a scripting language such as Python or R.
 </li>
 <li>
 Comfort with data warehouses and big data technologies at consumer scale such as Redshift, Snowflake, Big Query, etc.
 
 
 
 </li>
 </ul>
 
 Bonus Points
 
 
 
 
 <ul>
 <li>
 Master&rsquo;s or Doctorate degree in a quantitative field (e.g. Statistics, Business Analytics, Data Science, Mathematics, Economics, Engineering, or Computer Science)
 </li>
 <li>
 Experience in gaming or digital media
 
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 
 <ul>
 <li>
 Medical, Dental, Vision &amp; Disability Insurance
 </li>
 <li>
 401(k)
 </li>
 <li>
 Maternity &amp; Parental Leave
 </li>
 <li>
 Flexible PTO
 </li>
 <li>
 Amazon Employee Discount
 
 
 
 </li>
 </ul>
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 
 Job ID: TW9095
 
 
 The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
 
 
 US, CA, San Francisco
 
 
 $157,300&mdash;$212,800 USD
 
 
 
 Twitch is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
 
 
 
 
 Twitch values your privacy. Please consult our Candidate Privacy Notice, for information about how we collect, use, and disclose personal information of our candidates.
 
</div>

Data Scientist

Triumph

<div>
 
 The Role
 
 
 
 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.
 
 
 
 What You'll Do
 
 
 
 <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>
 
 Qualifications
 
 
 
 <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>
 
 Preferred Qualifications
 
 
 
 <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>
 
 Why Triumph?
 
 
 
 <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: $200K - $400K
 
 
</div>

Genentech

<div><div><div>THE POSITION</div>
We advance science so that we all have more time with the people we love.
The Department of Cell and Tissue Genomics (CTG) is focused on developing and applying state of the art genomics technologies (e.g. single cell omics, high-content imaging, perturbations, etc) to solve key challenges in disease biology, target discovery, and translational medicine. We are seeking a highly talented, creative, and motivated computational biologist to analyze cutting-edge high-dimensional profiling and screening data, with a particular focus on high-content imaging, to decipher complex cellular circuits. The candidate will collaborate closely with members of the department to extract biological insights from diverse high dimensional data sets and support the development of new technologies, leveraging existing computational workflows and developing novel ones.
The Opportunity:
As an integral member of our dynamic team, you will be:<ul><li>
Analyzing high-content imaging data from novel technologies including optical pooled screens, spatial transcriptomics, and high-content perturbation screens, with the goal of extracting mechanistic insights into gene function and cellular phenotypes.</li><li>
Developing methods to analyze and interpret new types of perturbation data.</li><li>
Applying statistics and machine learning to investigate data and extract biological insights.</li><li>
Collaborating across diverse, cross-functional teams including experimentalists in CTG and the therapeutic areas and colleagues in the Computational Sciences Center of Excellence and the AI Biology &amp; Translation departments</li></ul>
Who You Are:<ul><li>
PhD in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field. Alternatively, a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area. Postdoctoral training is a plus.</li><li>
Strong publication record of biological discovery and/or methods development.</li><li>
Deep expertise in image analysis, including image processing, feature extraction, and morphological profiling. Familiarity with modern deep learning approaches (e.g., embeddings, foundation models) is a plus.</li><li>
Comfortable with the statistical principles behind current best practices in high-throughput data analysis.</li><li>
Fluent in Python and/or R.</li><li>
Excellent communication and presentation skills.</li><li>
Able to work successfully in cross-functional teams to collaboratively solve complex problems.</li><li>
Passionate about applying your analytical skills to understand health and disease.</li></ul>
Preferred Experience:<ul><li>
Experience with in situ data (FISH or ISS barcode calling).</li><li>
Familiarity with image analysis frameworks or libraries (e.g., CellProfiler).</li><li>
Experience with genomic data including single cell RNA-seq and perturbation screens is a plus.</li><li>
Experience with applying machine learning to high throughput datasets is a plus.</li></ul>
Relocation benefits are available for this posting.
The expected salary range for this position based on the primary location of California for Senior Scientist is $124,300- $230,900 and Principal Scientist is $143,200-$265,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Research Informatics
</div><div>Schedule
Full time
</div><div>Job Type
Regular
</div><div>Posted Date
Apr 10th 2026
</div><div>Job ID
202604-108731</div></ul></div></div></div></div>

Computational Scientist 3 - Cell & Tissue Genomics

OpenAI

<div>
 
 About The Team
 
 
 
 OpenAI&rsquo;s mission is to ensure AGI benefits all of humanity. The API organization is one of the highest-leverage ways we do that: we put frontier intelligence in the hands of builders who turn it into products, businesses, and services that reach people everywhere.
 
 
 We build the infrastructure and developer platform that makes that possible&mdash;so developers can reliably bring powerful AI into the real world, operate it safely at scale, and keep pushing what&rsquo;s possible. When we do our job well, we don&rsquo;t just ship an API. We enable thousands of teams to create new capabilities for millions of end users, accelerating progress across industries and communities.
 
 
 
 About The Role
 
 
 
 As a Data Scientist on the API team, you&rsquo;ll build the measurement systems that make our platform legible and improveable. You&rsquo;ll define the metrics that matter, identify and quantify developer friction, evaluate launches and platform changes, and translate data into product decisions that improve reliability and developer outcomes at scale.
 
 
 You&rsquo;ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements.
 
 
 This role is based in San Francisco. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Own the core KPI framework for the API platform, spanning developer adoption, engagement, retention, and platform health.
 </li>
 <li>
 Build end-to-end funnels that identify where developers succeed or get stuck&mdash;from first integration through scaling to production.
 </li>
 <li>
 Define and operationalize platform guardrails (e.g., reliability, latency, error rates, cost/efficiency) and connect them to user outcomes.
 </li>
 <li>
 Design and evaluate experiments and rollouts to quantify the impact of platform and product changes.
 </li>
 <li>
 Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct.
 </li>
 <li>
 Translate complex analysis into clear, actionable insights for leadership and cross-functional stakeholders.
 </li>
 <li>
 Develop and socialize dashboards, tools, and self-serve data products that help teams answer product questions quickly.
 </li>
 <li>
 Help establish data science standards and best practices for measuring AI platform performance and developer success.
 </li>
 <li>
 Partner with other data scientists across the company to share learnings and raise the bar on measurement and decision-making.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You Have
 
 
 
 <ul>
 <li>
 10+ years of experience in data science roles within product or technology organizations (platform or developer-facing experience is a plus).
 </li>
 <li>
 Expertise in statistics and causal inference, applied in both experimentation and observational studies.
 </li>
 <li>
 Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation.
 </li>
 <li>
 Proven experience designing and interpreting experiments and making statistically sound recommendations.
 </li>
 <li>
 Experience building datasets, metrics, and data pipelines that power production decision-making.
 </li>
 <li>
 Experience developing and extracting insights from business intelligence tools (e.g., Tableau) and building self-serve solutions.
 </li>
 <li>
 Strong product sense and an impact-driven mindset: you turn ambiguity into crisp frameworks that drive roadmap decisions.
 </li>
 <li>
 Ability to build relationships with diverse stakeholders and cultivate strong partnerships across Product, Engineering, Research, and GTM teams.
 </li>
 <li>
 Strong communication skills, including the ability to bridge technical and non-technical audiences.
 </li>
 <li>
 Ability to operate effectively in a fast-moving, ambiguous environment with limited structure.
 </li>
 <li>
 Are consistently among the first to adopt the latest AI tools, you use them daily to increase your own throughput, and you proactively turn them into durable workflows that change how your team and org operate.
 
 
 </li>
 </ul>
 
 Nice-to-haves
 
 
 
 <ul>
 <li>
 Experience with developer platforms, APIs/SDKs, or usage-based products.
 </li>
 <li>
 Experience with platform reliability analytics, incident impact measurement, or performance/cost optimization.
 </li>
 <li>
 Familiarity with AI evaluation and quality measurement systems (online/offline evals, human-in-the-loop, safety/quality guardrails).
 
 
 </li>
 </ul>
 
 Why it matters
 
 
 
 When developers build on OpenAI, they put our platform into products that touch millions of people. API Data Science ensures we make the right bets, operate with rigor, and continuously raise reliability and usability as the platform scales. This is a unique opportunity to shape how frontier AI is measured, improved, and delivered through a platform that powers the next generation of AI products.
 
 
 
 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.
</div>

Data Scientist, API

Shipt

<div>
 
 Impact
 
 
 
 As a Data Scientist specializing in geospatial intelligence, you will help power the next generation of final-mile logistics. This role will develop advanced models and data systems that leverage location, routing, traffic, and spatial signals to improve delivery success, reduce operational costs, and create a better experience for customers and drivers.
 
 
 In this role you will work with large-scale GPS traces, mapping data and geospatial datasets. You will collaborate with product ,managers, logistic operators and software engineers to turn models into real-world systems. You will design experiments and translate complex geospatial insights into actionable operational decisions.
 
 
 
 
 What You&rsquo;ll Need to Be Successful
 
 
 
 
 <ul>
 <li>
 MS or PhD in Statistics, Applied Mathematics, Computer Science, or other quantitative fields
 </li>
 <li>
 2+ years of experience with geospatial data (ex. GPS traces, spatial indexing systems, or routing systems)
 </li>
 <li>
 Strong understanding of predictive modeling, feature engineering, experimentation and causal inference
 </li>
 <li>
 Strong Python skills with experience in libraries such as: pandas, scikit-learn, PyTorch or TensorFlow
 </li>
 <li>
 Ability to work with large datasets and distributed systems (ex. Spark, BigQuery, Snowflake, etc.)
 
 
 </li>
 </ul>
 
 Pay Range: $76,100- $130,000
 
 
 
 
 
 Please note that the salary range above is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location.
 
 
 
 
 
 Skills &amp; Education
 
 
 
 This list includes key skills used in this job but is not inclusive of all skills needed for the role. Please see any required education below.
 
 
 Data Science, Geospatial Data, Geospatial Modeling, Python (Programming Language)
 
 
 Bachelor's Degree or equivalent experience&emsp14;| Required
 
 
 
 Work Arrangement
 
 
 
 Shipt considers candidates located near a Shipt office or workspace in Birmingham, San Francisco, or Minneapolis to be hybrid, which means that they have the flexibility to work from home (with leader approval) or at a Shipt office in order to facilitate the ability to innovate, collaborate, and spark team connections. In-office expectations will vary by role and leader. Certain roles may require in-office presence on a full-time basis. Please work with your recruiter to learn more about the classification of this role.
 
 
 
 About Shipt
 
 
 
 Shipt is a retail tech company that connects people to reliable, high-quality delivery with a personal touch. Shipt connects customers to the things they want from the stores they love, retail businesses to more satisfied customers, and workers to new earning opportunities.
 
 
 At Shipt, we aim to put our team first to boost a sense of belonging, spark opportunities for growth, provide unique benefits and commit to giving back to our communities in ways that make life better, both personally and professionally. We understand that our service, our culture, and our connection to our communities are only made better by every single person who shows up to work here every day. Learn More.
 
 
 Shipt is an independently operated, wholly owned subsidiary of Target Corporation and available in more than 5,000 U.S. cities. Shipt was founded and is headquartered in Birmingham, Alabama. For more information, please visit Shipt&rsquo;s company site at Shipt.com.
 
 
 
 We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, color, national origin, ethnicity, religion or religious belief, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, military or veteran status, disability, or any other characteristic protected by law.
 
 
 
 
 Please inform your recruiting contact upon initial connection if you need a reasonable accommodation. If you need assistance filling out a job application, please complete this form.
 
 
 For technical interviews, Shipt uses an online coding platform. In the event you may need a reasonable accommodation to use the online coding platform, please connect with your recruiter.
 
 
 
 
 Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
 
 
 
 
 Employees (and eligible family members) are covered by medical, dental, vision and more. Employees may enroll in our company&rsquo;s 401k plan. Employees will also be eligible to receive discretionary vacation for exempt team members, paid holidays throughout the calendar year and paid sick leave. Other compensation includes eligibility for an annual bonus and the potential for restricted stock units based on role.
 
</div>

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>

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