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data scientist integrity measurement

OpenAI

<div>
 
 About The Team
 
 
 
 The Applied Foundations team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. Our team is at the front lines of defending against financial abuse, scaled attacks, and other forms of misuse that could undermine the user experience or harm our operational stability
 
 
 The Integrity pillar within Applied Foundations is responsible for the scaled systems that help identify and respond to bad actors and harm on OpenAI&rsquo;s platforms. As the systems that address some of our most severe usage harms become more mature, we&rsquo;re adding data scientists to help us measure robustly the prevalence of these problems and the quality of our response to them.
 
 
 
 About The Role
 
 
 
 We are looking for experienced trust and safety data scientists to help us improve, productionise and monitor measurement for complex, actor- and sometimes network-level harms. A data scientist in this role will own measurement and metrics across several established harm verticals, including estimating prevalence for on-platform (and sometimes off-platform!) harm, and analyses to identify gaps and opportunities in our responses.
 
 
 This role is based out of our San Francisco or New York office and may involve resolving urgent escalations outside of normal work hours. Many harm areas may involve sensitive content, including sexual, violent, or otherwise-disturbing material.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Own measurement and quantitative analysis for a group of severe, actor- and network-based usage harm verticals.
 </li>
 <li>
 Develop and implement AI-first methods for prevalence measurement and other productionised safety metrics, which may necessarily include off-platform indicators or other non-standard datasets.
 </li>
 <li>
 Build metrics that can be used for goaling or A/B tests when prevalence or other top line metrics are not suitable.
 </li>
 <li>
 Own dashboards and metrics reporting for harm verticals.
 </li>
 <li>
 Conduct analyses and generate insights that inform improvements to review, detection, or enforcement, and that influence roadmaps.
 </li>
 <li>
 Optimise LLM prompts for the purpose of measurement.
 </li>
 <li>
 Collaborate w/ other safety teams to understand key safety concerns and create relevant policies that will support safety needs.
 </li>
 <li>
 Provide metrics for leadership and external reporting.
 </li>
 <li>
 Develop automation to scale yourself, leveraging our agentic products.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Are a senior DS with trust and safety experience that can drive measurement direction.
 </li>
 <li>
 Have deep statistics skills, specifically around sampling methods and prevalence estimation of complicated problem areas (ideally activity- rather than content-based).
 </li>
 <li>
 Have experience working with severe and sensitive harm areas like child safety or violence.
 </li>
 <li>
 Are an excellent communicator, and have strong cross-functional collaboration skills.
 </li>
 <li>
 Are capable in data programming languages (R or python, SQL).
 </li>
 <li>
 (Ideally) have experience with AI harms or leveraging AI for measurement.
 
 
 </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 - $385K
</div>

Data Scientist, Integrity Measurement

<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

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>

Data Scientist

Early Warning Services

<div>At Early Warning, we&rsquo;ve powered and protected the U.S. financial system for over thirty years with cutting-edge solutions like Zelle&reg;, Paze℠, and so much more. As a trusted name in payments, we partner with thousands of institutions to increase access to financial services and protect transactions for hundreds of millions of consumers and small businesses.
Positions located in Scottsdale, San Francisco, Chicago, or New York follow a hybrid work model to allow for a more collaborative working environment.
Candidates responding to this posting must independently possess the eligibility to work in the United States, for any employer, at the date of hire. This position is ineligible for employment Visa sponsorship.
Overall Purpose
The Technical Product Manager is a key role on our Data &amp; AI team charged with developing the next generation of analytical technology for Early Warning Services. This role will focus on our data capabilities to improve both R&amp;D and productionalization of predictive models. 
The Technical Product Manager collaborates closely with Analytics, MLOps, Engineering team members and other business stakeholders to translate enterprise-wide stakeholder needs into technical model, data, reporting and analytics requirements, working across technology teams to facilitate the development of internal-facing data platforms, products or capabilities. 
Essential Functions<ul><li>
Define and deliver roadmap and technical requirements for data and analytics capabilities, processes, and tools to enable prioritized use cases across the enterprise.</li><li>
Scope and prioritize activities based on business and user impact which defines product enhancements for both short-term and long-term.</li><li>
Gain a deep understanding of end-user needs and experience (internal data consumers), identify and fill product gaps and generate new ideas that grow adoption and improve user experience.</li><li>
Gather requirements for the Data Technology team on data processing and storage to facilitate a variety of model and analytics use cases such as effective analysis and reporting, data science exploration and model development, and data quality and anomaly detection.</li><li>
Set and achieve success metrics to meaningfully improve business results, focusing on what success looks like for our internal data consumers and how accessible data and insights could help them deliver enterprise value.</li><li>
Enforce data quality standards and processes and ensure that data governance policies, data lineage and metadata management are integral components of data product development.</li><li>
Support the implementation, measurement, and activation of data-driven use cases.</li><li>
Support the integration of strong data governance, risk, and security controls.</li><li>
Support the company&rsquo;s commitment to risk management and protect the integrity and confidentiality of systems and data.</li><li>
Support the integration of MLOps workflows and data pipelines that enable model deployment and monitoring.</li><li>
Participate in defining RAG and LLM-based product capabilities.</li><li>
Ensure basic compliance with model governance, including lineage, metadata, model monitoring, and bias documentation.</li><li>
Collaborate with AI and MLOps Engineers to support model deployment pipelines on AWS and on-prem technologies.</li></ul> 
Minimum Qualifications<ul><li>
Education and/or experience typically obtained through completion of a bachelor&rsquo;s degree in STEM or related field.</li><li>
5+ years' experience or related experience in product management, data management, or consulting with a proven record of high performance, preferably with experience building data and analytics products.</li><li>
3+ years' experience with direct hands-on responsibility working with data or data teams (data engineers, data scientists, software developers, data analysts, etc.), business stakeholders and end-users.</li><li>
Strong business intuition and the technical ability to understand, design, and explain complex product and data strategies to both business and technical audiences.</li><li>
Proficiency with software development methodologies such as Agile and experience working with Scrum teams and working with Agile tools such as Jira.</li><li>
Strong project and stakeholder management with the ability to work effectively with cross functional teams with diverse skill sets across all levels of the organization.</li><li>
Excellent communications skills, both oral and written.</li><li>
Hands-on experience writing, reviewing, and tuning SQL, Spark, and Python.</li><li>
Comfort with product analytics and data visualization tools (e.g., Tableau).</li><li>
Background and drug screen.</li></ul> 
Preferred Qualifications<ul><li>
Master&rsquo;s degree in STEM or related field.</li><li>
Deep understanding of foundational data and analytics concepts.</li><li>
Proven track record of managing all aspects of a successful product throughout its lifecycle, with experience in launching brand new products.</li><li>
Strong understanding of data management requirements in a regulated industry.</li><li>
Experience in financial institutions, particularly payments, identity, and fraud analytics.</li><li>
Experience working with terabyte size datasets.</li><li>
Experience with change management and moving from on-prem to cloud.</li><li>
Hands-on experience with Python or R, as a data scientist.</li><li>
Understanding of data science tools and concepts and experience directly enabling data science teams or delivering data science use cases.</li><li>
Experience with: AWS, Salesforce, SQL Server, Hive, Spark, SQL, and data architecture tools such as HDFS, Aerospike, ElasticSearch, Kafka, EKS.</li><li>
Deep understanding of best practices and unique data and analytics requirements.</li></ul>
Physical Requirements
Early Warning works together in a highly collaborative office environment. As such, working conditions consist of a normal office environment. Work is primarily sedentary and requires extensive use of a computer and involves sitting for periods of approximately four hours. Work may require occasional standing, walking, kneeling and reaching. Must be able to lift 10 pounds occasionally and/or negligible amount of force frequently. Requires visual acuity and dexterity to view, prepare, and manipulate documents and office equipment including personal computers. Requires the ability to communicate with internal and/or external customers.
Employee must be able to perform essential functions and physical requirements of position with or without reasonable accommodation.
Candidates responding to this posting must independently possess the eligibility to work in the United States at the date of hire. 
The base pay scale for this position in: 
Phoenix, AZ in USD per year is: $106,000 - $130,000. 
San Francisco, CA in USD per year is: $128,000 - $156,000. 
Additionally, candidates are eligible for a discretionary incentive plan and benefits.
This pay scale is subject to change and is not necessarily reflective of actual compensation that may be earned, nor a promise of any specific pay for any specific candidate, which is always dependent on legitimate factors considered at the time of job offer. Early Warning Services takes into consideration a variety of factors when determining a competitive salary offer, including, but not limited to, the job scope, market rates and geographic location of a position, candidate&rsquo;s education, experience, training, and specialized skills or certification(s) in relation to the job requirements and compared with internal equity (peers). The business actively supports and reviews wage equity to ensure that pay decisions are not based on gender, race, national origin, or any other protected classes.
Some of the Ways We Prioritize Your Health and Happiness<ul><li> 
Healthcare Coverage &ndash; Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health &amp; dependent care expenses.</li><li>
401(k) Retirement Plan &ndash; Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.</li><li>
Paid Time Off &ndash; Flexible Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day.</li><li>
12 weeks of Paid Parental Leave
</li><li>Maven Family Planning &ndash; provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work.</li></ul> 
And SO much more! We continue to enhance our program, so be sure to check our Benefits page here for the latest. Our team can share more during the interview process!
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Early Warning Services, LLC (&ldquo;Early Warning&rdquo;) considers for employment, hires, retains and promotes qualified candidates on the basis of ability, potential, and valid qualifications without regard to race, religious creed, religion, color, sex, sexual orientation, genetic information, gender, gender identity, gender expression, age, national origin, ancestry, citizenship, protected veteran or disability status or any factor prohibited by law, and as such affirms in policy and practice to support and promote equal employment opportunity and affirmative action, in accordance with all applicable federal, state, and municipal laws. The company also prohibits discrimination on other bases such as medical condition, marital status or any other factor that is irrelevant to the performance of our employees.</div>

Technical Product Manager - Data

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

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

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Join us at the Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. 
 
The Worldwide Sustainability (WWS) organization capitalizes on Amazon&rsquo;s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable. 
 
Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. 
 
The Sustainability Science and Innovation team is looking for a Sr. Applied Scientist to collaborate closely with Economists and Environmental Scientists to build the AI/ML foundation of the future. You will define strategy and implement tooling to identify, ingest, harmonize, store, and maintain strategic models and data from both internal and external sources. 
These models and datasets must cover a wide range of topics in emerging areas and applications of AI for sustainability. This AI solutions development will support Amazon-wide sustainability initiatives like carbon footprint, climate risk monitoring, and social responsibility through the supply chain. 
 
These datasets must cover a wide range of topics such as geographic regions and data formats to unlock foundational AI research in emerging areas and applications. These solutions development will support Amazon-wide sustainability initiatives like carbon footprinting, climate risk monitoring, and social responsibility through the supply chain. 
 
If you see yourself as a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you. You don't necessarily have to be an expert in sustainability and climate domains. 
 
Key job responsibilities 
<ul><li>Designing, implementing, and maintaining data and AI/ML infrastructure to support a wide variety of large and complex data sets, ensuring high performance, availability, and integrity.</li><li>Identifying and solving data needs for Gen AI and foundational model training and benchmarking for tasks across the sustainability domain.</li><li>Developing and optimizing robust data pipelines for internal data from sources such as Product Lifecycle Management tools, Product Details (images, text, and structured data), Inventory Management Platforms, and financial systems.</li><li>Design and implement web-scale data collection for images, text, structured data across locations and sustainability domains.</li><li>Develop comprehensive monitoring, alarming, and data quality controls for all of the above.</li><li>Partnering with Scientists and Software Engineers to create our data collection strategy and ML Ops best practices.</li></ul> 
About the team 
Diverse Experiences: 
World Wide Sustainability values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying. 
 
Inclusive Team Culture: 
It&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive diversity) conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth: 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance: 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
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. 
USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, WW Sustainability

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