data scientist, product analytics Jobs in San Francisco

data scientist, product analytics

financial analyst

advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai data engineer (agent platform) Jobs in San Francisco

ai data engineer (agent platform)

ai research engineer Jobs in San Francisco

ai research engineer

analytical data scientist

Data Scientist, Product Analytics

<div>
 We are seeking experienced Data Scientists to join our team and drive impact across various product areas. As a Data Scientist, you will collaborate with cross-functional partners to identify and solve complex problems using data and analysis. Your role will involve shaping product development, quantifying new opportunities, and ensuring products bring value to users and the company. You will guide teams using data-driven insights, develop hypotheses, and employ rigorous analytical approaches to test them. You will tell data-driven stories, present clear insights, and build credibility with stakeholders. By joining our team, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond.
 
 
 Data Scientist, Analytics (Technical Leadership) Responsibilities:
 
 
 <ul>
 <li>
 Work with complex data sets to solve challenging problems using analytical and statistical approaches
 </li>
 <li>
 Apply technical expertise in quantitative analysis, experimentation, and data mining to develop product strategies
 </li>
 <li>
 Identify and measure success through goal setting, forecasting, and monitoring key metrics
 </li>
 <li>
 Partner with cross-functional teams to inform and execute product strategy and investment decisions
 </li>
 <li>
 Build long-term vision and strategy for programs and products
 </li>
 <li>
 Collaborate with executives to define and develop data platforms and instrumentation
 </li>
 <li>
 Effectively communicate insights and recommendations to stakeholders
 </li>
 <li>
 Define success metrics, forecast changes, and set team goals
 </li>
 <li>
 Support developing roadmaps and coordinate analytics efforts across teams
 
 
 </li>
 </ul>
 Minimum Qualifications:
 
 
 <ul>
 <li>
 Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
 </li>
 <li>
 Mathematics, Statistics, Operations Research) 5+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical/mathematical software (e.g. R, SAS, Matlab)
 </li>
 <li>
 8+ years of work experience leading analytics work in IC capacity, working collaboratively with Engineering and cross-functional partners, and guiding data-influenced product planning, prioritization and strategy development
 </li>
 <li>
 Experience working effectively with and leading complex analytics projects across multiple stakeholders and cross-functional teams, including Engineering, PM/TPM, Analytics and Finance
 </li>
 <li>
 Experience with predictive modeling, machine learning, and experimentation/causal inference methods
 </li>
 <li>
 Experience communicating complex technical topics in a clear, precise, and actionable manner
 
 
 </li>
 </ul>
 Preferred Qualifications:
 
 
 <ul>
 <li>
 10+ years of experience communicating the results of analyses to leadership teams to influence the strategy
 </li>
 <li>
 Masters or Ph.D. Degree in a quantitative field
 </li>
 <li>
 Bachelor's Degree in an analytical or scientific field (e.g. Computer Science, Engineering, Mathematics, Statistics, Operations Research)
 </li>
 <li>
 10+ years of experience doing complex quantitative analysis in product analytics
 </li>
 <li>
 Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
 </li>
 <li>
 Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
 </li>
 <li>
 Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
 
 
 </li>
 </ul>
 About Meta:
 
 
 Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today&mdash;beyond the constraints of screens, the limits of distance, and even the rules of physics.
 
 
 Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
 
 
 Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
 
 
 $210,000/year to $281,000/year + bonus + equity + benefits
 
 
 Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
</div>

Data Scientist, Analytics (Technical Leadership)

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>

Samba TV

<div>
 
 
 Samba is an AI-powered media intelligence company on a mission to give marketers the complete picture of their audiences. Our AI indexes media consumption across millions of smart TVs and 2.5 billion web pages, combining that data with third-party signals through the Samba Knowledge Graph, a map of the real interests, behaviors, and purchase intent of 1.5 billion user profiles globally. Brands, agencies, publishers, and platforms use Samba to make smarter decisions across every stage of the marketing funnel.
 
 
 
 
 
 
 
 
 
 
 ABOUT THE ROLE
 
 
 
 
 
 
 We are looking for a hands-on Data Scientist to own and deliver complex measurement science and modeling work at the core of our measurement and audience sciences products.&nbsp;
 
 
 
 
 
 The role requires a deep, first-principles understanding of data science and machine learning &amp;mdash; not just the ability to apply libraries, but the ability to reason clearly about model behavior, articulate trade-offs between approaches, and make defensible methodological decisions under ambiguity. This is emphatically a coding role &amp;mdash; you will spend the majority of your time writing production-quality Python, building and evaluating models on large-scale viewership and web data, and delivering end-to-end ML solutions.
 
 
 
 
 
 You will work closely with Data Engineering, Product, and go-to-market teams.
 
 
 
 
 
 
 
 
 
 WHAT YOU'LL DO
 
 
 <ul>
 
 <li>
 
 
 
 Write and own production-quality Python code end-to-end &amp;mdash; well-structured, tested, documented, and built to last; PySpark proficiency is essential for working with Samba's billion-row viewership datasets
 
 
 
 </li>
 
 <li>
 
 
 
 Design, build, and deploy measurement models and statistical frameworks that power Samba&rsquo;s campaign measurement, reach/frequency estimation, and cross-platform attribution products
 
 
 
 </li>
 
 <li>
 
 
 
 Apply the right statistical and ML technique to the right problem &amp;mdash; drawing from hierarchical models, Bayesian inference, gradient boosting, regularized regression, causal ML, and probabilistic record linkage &amp;mdash; and clearly articulate the reasoning behind your choices
 
 
 
 </li>
 
 <li>
 
 
 
 Build and evaluate multi-touch and multi-channel attribution models; apply Causal ML methods &amp;mdash; counterfactual modeling, meta-learners (S-learner, T-learner, X-learner), and heterogeneous treatment effect estimation &amp;mdash; to advertising and viewership measurement problems
 
 
 
 </li>
 
 <li>
 
 
 
 Partner with Data Engineering to define data requirements, validate pipelines, and ensure model inputs are reliable, scalable, and production-ready
 
 
 
 </li>
 
 <li>
 
 
 
 Lead technical design reviews and contribute meaningfully to architecture decisions across the Data Science team
 
 
 
 </li>
 
 <li>
 
 
 
 Mentor junior Data Scientists through code review, pairing, and structured technical feedback &amp;mdash; raising the team's technical floor
 
 
 
 </li>
 
 <li>
 
 
 
 Communicate measurement methodologies and findings clearly to technical and non-technical audiences, including senior leadership and external clients
 
 
 
 </li>
 
 </ul>
 
 
 
 
 
 WHO ARE YOU
 
 
 <ul>
 
 <li>
 
 
 
 5-7 years of professional data science experience &amp;mdash; hands-on, delivery-focused, and measurable in shipped models and production systems
 
 
 
 </li>
 
 <li>
 
 
 
 Expert-level Python &amp;mdash; clean, modular, testable, production-ready code is your standard, not your aspiration
 
 
 
 </li>
 
 <li>
 
 
 
 Advanced PySpark and Databricks &amp;mdash; comfortable building and optimizing data pipelines and ML workflows on billion-row datasets
 
 
 
 </li>
 
 <li>
 
 
 
 Deep, first-principles command of statistics and ML &amp;mdash; you can explain from the ground up how these models work and you apply this understanding to make better modeling decisions
 
 
 
 </li>
 
 <li>
 
 
 
 Solid grasp of experimental design &amp;mdash; A/B testing, randomization, power analysis, and the conditions under which observational causal inference is appropriate
 
 
 
 </li>
 
 <li>
 
 
 
 Fluent in the full ML lifecycle: feature engineering, model evaluation, deployment pipelines, drift monitoring, and iterative improvement in production
 
 
 
 </li>
 
 <li>
 
 
 
 Hands-on experience with uplift modeling, synthetic control, difference-in-differences, or propensity-based approaches applied to advertising or media outcomes
 
 
 
 </li>
 
 <li>
 
 
 
 Strong ownership mindset &amp;mdash; you drive projects independently and are comfortable owning your models from data exploration through production delivery, with minimal hand-holding.
 
 
 
 </li>
 
 <li>
 
 
 
 Clear communicator &amp;mdash; able to translate statistical reasoning and model behavior into language that drives decisions with product, engineering, and leadership
 
 
 
 </li>
 
 </ul>
 
 
 <ul>
 
 <li>
 
 
 
 Experience with multi-touch attribution (MTA) or multi-channel attribution modeling &amp;mdash; understanding of the limitations of rule-based approaches and the methodological trade-offs of data-driven alternatives
 
 
 
 </li>
 
 <li>
 
 
 
 Hands-on experience with Causal ML methods &amp;mdash; counterfactual modeling, meta-learners, and heterogeneous treatment effect estimation &amp;mdash; applied to advertising or media measurement outcomes
 
 
 
 </li>
 
 <li>
 
 
 
 Direct exposure to TV or digital viewership data &amp;mdash; ACR signals, STB data, viewership panels, or cross-platform measurement (linear + CTV/OTT)
 
 
 
 </li>
 
 <li>
 
 
 
 Familiarity with the measurement
 
 
 
 </li>
 
 <li>
 
 
 
 t vendor landscape (Nielsen, Comscore, VideoAmp, iSpot) and industry standards (MRC, GRP/TRP frameworks)
 
 
 
 </li>
 
 <li>
 
 
 
 Advanced degree (MS or PhD) in Statistics, Mathematics, Computer Science, or a related quantitative field &amp;mdash; or equivalent depth demonstrated through work
 
 
 
 </li>
 
 </ul>
 
 
 
 
 
 
 
 
 
 Samba is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.&nbsp;&nbsp;We strive to empower connection with one another, reflect the communities we serve, and tackle meaningful projects that make a real impact.
 
 
 
 
 &nbsp;
 
 
 
 
 Samba may collect personal information directly from you, as a job applicant, Samba may also receive personal information from third parties, for example, in connection with a background, employment or reference check, in accordance with the applicable law.
 
 
 For further details, please see Samba's
 
 
 Applicant Privacy Policy
 
 
 .
 
 
 For residents of the EU , Samba Inc. is the data controller.
 
 
 
 
 Samba expects to offer a base salary between
 
 $150,000 - $180,000 USD
 
 per year for roles to be performed in San Francisco or California; actual base salary offered will depend on various factors including but not limited to location, experience, and performance. Base salary is just one component of Samba's total compensation package for employees. Other rewards may include bonuses, short-term incentives and long-term incentives. In addition, Samba provides health insurance, wellness offerings, life and disability insurance, a retirement savings plan, paid holidays and paid time off (PTO), and other employee benefits.
</div>

Data Scientist

Eli Lilly

<div>At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We&rsquo;re looking for people who are determined to make life better for people around the world.<h1 class="jobSectionHeader">
The Opportunity</h1>
We are building something unprecedented &mdash; an AI foundation that will push the frontier on what is possible today across drug discovery research, from target identification and disease biology through translational science.
The Applied Intelligence for Discovery (AI4D) team is a newly formed group within Lilly Research Laboratories that operates at the intersection of scientific delivery and core platform development. AI4D&rsquo;s mission is connecting scientists to petabyte-scale data through natural language interfaces, automated analysis workflows, and intelligent search &mdash; and to convert early deployments into repeatable system standards and evaluation practices that scale across therapeutic areas.
As a Scientific Data Engineer, you will close that gap. You will build the semantic layer, data harmonization infrastructure, AI-ready data products, and lakehouse architecture that bridge how data is stored and how AI systems need to consume it. You will be working at the intersection of the data infrastructure team and the generative AI engineers who build the systems scientists interact with.<h1 class="jobSectionHeader">
Responsibilities</h1><h2 class="jobSectionHeader">
Data Harmonization and Lakehouse Architecture</h2><ul><li>
Design and build the data architecture that transforms raw and processed omics data into harmonized, AI-consumable layers</li><li>
Build and optimize ETL/ELT pipelines that produce denormalized views, pre-computed aggregations, embedding-ready text representations, and feature stores optimized for AI system consumption</li><li>
Implement data quality monitoring, automated profiling, and validation checks across harmonization layers</li><li>
Create versioned, reproducible data snapshots that support model training, evaluation, and audit requirements in a regulated environment</li><li>
Partner with the teams to extend harmonization patterns as data modalities expand beyond genomics and proteomics into spatial transcriptomics, perturbational data (Perturb-Seq), single-cell, and digital pathology</li></ul><h2 class="jobSectionHeader">
Semantic Layer and Schema Engineering</h2><ul><li>
Design and maintain a semantic layer over Lilly&rsquo;s multi-omics databases that enables AI systems</li><li>
Create comprehensive schema documentation: table descriptions, column-level annotations, relationship mappings, business logic rules, and domain-specific constraints (e.g., statistical thresholds, unit conventions, experimental design metadata)</li><li>
Develop gold-standard question/SQL pairs for each major database, in collaboration with computational biologists and Generative AI Engineers, to serve as training data, few-shot examples, and evaluation benchmarks</li><li>
Build and maintain a data dictionary and ontology mapping layer that translates how scientists think and speak about data (gene names, pathway terms, assay types) into how the data is physically stored</li></ul><h2 class="jobSectionHeader">
AI-Ready Data Products</h2><ul><li>
Build and manage vector embedding pipelines for scientific documents, study metadata, and structured data descriptions to power RAG-based retrieval</li><li>
Build integration pipelines that connect heterogeneous data sources &mdash; omics databases, internal publications, electronic lab notebooks, assay results, and clinical annotations &mdash; into a unified, queryable layer</li><li>
Develop and enforce metadata standards that ensure new data sources are AI-accessible from the point of ingestion, not retroactively</li><li>
Design data products that serve multiple consumption patterns: direct SQL access for computational biologists, structured feeds for ML training pipelines, and semantic interfaces for LLM-powered tools</li></ul><h1 class="jobSectionHeader">
Qualifications</h1><ul><li>
Bachelors degree in Computer Science, Data Engineering, Bioinformatics, or a related field + 8 years data engineering experience OR Masters degree and 5 years data engineering experience</li><li>
Demonstrated expertise in building data pipelines, ETL/ELT workflows, and data products that serve downstream AI/ML systems</li></ul><h1 class="jobSectionHeader">
Additional Skills/Preferences</h1><ul><li>
Phd in data or related field</li><li>
Strong SQL skills and experience with complex relational database schemas (hundreds of tables, multi-level joins, domain-specific conventions)</li><li>
Experience with modern data platform technologies, including at least one of: Databricks, Snowflake, or equivalent lakehouse platforms</li><li>
Experience with modern data engineering tools: dbt, Spark, Airflow, or similar orchestration and transformation frameworks</li><li>
Proficiency in Python for data processing, scripting, and pipeline development</li><li>
Experience with cloud data platforms (AWS preferred: Redshift, Athena, Glue, S3, or similar)</li><li>
Familiarity with at least one of: vector databases, embedding pipelines, or semantic layer tooling</li><li>
Strong communication skills &mdash; you can work effectively with both engineers who think in schemas and scientists who think in biology</li><li>
Experience with biomedical or scientific data: omics datasets (RNA-seq, proteomics, GWAS), clinical data, or laboratory information management systems</li><li>
Experience in pharmaceutical, biotech, or life sciences environments</li></ul><ul><li>
Familiarity with biomedical ontologies and controlled vocabularies (Gene Ontology, MeSH, ChEBI, HGNC) and their application to data integration</li><li>
Experience building data products that serve AI/ML systems &mdash; feature stores, training datasets, evaluation benchmarks, or semantic annotations for text-to-SQL</li><li>
Knowledge of data governance practices in regulated industries: data lineage, access controls, versioning, and auditability</li><li>
Experience with knowledge graph technologies (Neo4j, Amazon Neptune, RDF/SPARQL) or graph-based data modeling</li><li>
Deep experience with Databricks ecosystem: Unity Catalog for data governance, Delta Lake for ACID transactions, MLflow integration, and Databricks SQL for analytics workloads</li><li>
Experience designing data architectures that bridge traditional bioinformatics workflows (Nextflow, R/Bioconductor) with modern lakehouse consumption patterns</li></ul>
Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.
Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status. 
Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia Network, Black Employees at Lilly, Chinese Culture Network, Japanese International Leadership Network (JILN), Lilly India Network, Organization of Latinx at Lilly (OLA), PRIDE (LGBTQ+ Allies), Veterans Leadership Network (VLN), Women&rsquo;s Initiative for Leading at Lilly (WILL), enAble (for people with disabilities). Learn more about all of our groups.
Actual compensation will depend on a candidate&rsquo;s education, experience, skills, and geographic location. The anticipated wage for this position is
$166,500 - $266,200
Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for medical, dental, vision and prescription drug benefits; flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts); life insurance and death benefits; certain time off and leave of absence benefits; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly&rsquo;s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.
#WeAreLilly</div>

Advisor - Scientific Data Engineer

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

MrBeast

<div><div><h3 class="jobSectionHeader">About Us</h3>

Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.</div>
Senior Data Scientist, Customer Data &amp; Marketing

Primary: Bay Area (San Francisco/Peninsula) | Secondary: NYC
<h1 class="jobSectionHeader">
About Us</h1>

Beast Industries is a multifaceted media and entertainment company founded by Jimmy Donaldson, popularly known as MrBeast, the most watched person in the world. Renowned for revolutionizing digital content creation, Beast Industries encompasses a diverse portfolio of ventures that extend far beyond its origins on YouTube. With a mission to entertain, inspire, and create significant social impact, Beast Industries operates across various domains including digital media, philanthropy, consumer products, and innovative business initiatives. At Beast Industries, we believe in the transformative power of digital media and its potential to entertain, educate, and effect positive change. Our commitment to innovation, creativity, and philanthropy drives us to explore new frontiers, create unforgettable experiences, and build a legacy that inspires future generations.

Location: Bay Area (San Francisco / Peninsula) Reports to: Director of Engineering Team: Data Science
<h1 class="jobSectionHeader">
The Opportunity</h1>

We are building a first-of-its-kind consumer membership ecosystem from the ground up &mdash; and as we centralize CRM, loyalty, and marketing across every line of business at Beast, the customer data behind it becomes one of the most valuable assets in the company. As our Senior Data Scientist for Customer Data &amp; Marketing, you will be a foundational hire on the Data Science team, sitting in the central org and working across LOBs to turn that data into decisions, experiments, and compounding business impact.

This is a hands-on, cross-functional role. You'll run experiments, build measurement, and partner with marketing, product, and LOB leaders so every campaign, loyalty program, and CRM motion is grounded in real evidence &mdash; at 100M+ user scale.
<h1 class="jobSectionHeader">
The Product</h1>

You will be the data science anchor underneath a centralized customer data, CRM, loyalty, and marketing stack that serves every LOB at Beast. Your surface area includes:
<ul>
<li>Experimentation &amp; Analytics: The experimentation platform, measurement framework, and decision-making muscle that every LOB will lean on &mdash; A/B tests, holdouts, causal analysis, and the judgment to call what actually worked.</li>
<li>CRM, Loyalty &amp; Marketing: Segmentation, targeting, lifecycle analytics, and performance measurement across the centralized CRM and loyalty stack &mdash; so membership, Feastables, and every other LOB are operating off the same playbook.</li>
<li>Customer Data at Scale: A unified view of the Beast audience built on top of our data &amp; identity platform, powering both the immediate marketing roadmap and the longer-term personalization and AI-native use cases.</li>
</ul><h1 class="jobSectionHeader">What You'll Do</h1>
<ul><li>Own the experimentation program end-to-end across LOBs &mdash; design, power, analyze, and call experiments in CRM, loyalty, and marketing, and make sure the org actually acts on the results.</li>
<li>Build the measurement foundation for centralized marketing: lifecycle metrics, campaign performance, loyalty program health, and the dashboards the business will run on.</li>
<li>Partner directly with marketing, product, and LOB leaders &mdash; membership, Feastables, and beyond &mdash; to translate business questions into crisp, quantitative answers.</li>
<li>Develop segmentation, targeting, and propensity models that drive real campaigns, not just slide decks.</li>
<li>Partner with Data &amp; Identity engineering to shape the customer data model &mdash; so the data you need for experimentation and marketing is actually there, and clean.</li>
<li>Set the analytical bar for the org: how we measure, how we experiment, and how we decide. Use AI-native tooling and coding agents to move faster than a traditional DS function.</li>
</ul><h1 class="jobSectionHeader">Who You Are</h1>
<ul><li>Experimentation-Obsessed: You've run rigorous experimentation programs inside consumer products at scale. You know when to run a test, when to trust a quasi-experiment, and when to stop arguing and ship.</li>
<li>Marketing &amp; CRM Fluent: You've worked shoulder-to-shoulder with marketing, lifecycle, and loyalty teams &mdash; and you know how to translate fuzzy business goals into concrete metrics, tests, and models.</li>
<li>Cross-Functional Operator: You're comfortable operating centrally and serving multiple LOBs. You can context-switch, prioritize ruthlessly, and build trust with stakeholders who don't all want the same thing.</li>
<li>AI-Native: You aren't just curious about AI; you are burning through tokens, using coding agents daily, and integrating modern AI tooling deeply into your analytical workflow.</li>
<li>Scrappy &amp; Scaled: You have the startup experience to build from zero with a nimble team, plus the big-tech exposure to know what good looks like at consumer scale.</li>
<li>Action-Oriented: You thrive in ambiguity and prefer shipping analyses that change decisions over producing beautiful but inert reports.</li></ul><div><h3 class="jobSectionHeader"> 
Benefits</h3>
<h4 class="jobSectionHeader">The Perks, Why Work On the MrBeast Team</h4>

We are redefining what entertainment and storytelling look like at global scale. Every piece of content we publish reaches millions and influences culture in real time. This is your opportunity to lead the team that decides how those moments come to life across every screen.
<ul>
<li>Competitive Salary</li>
<li>Generous Medical (Blue Cross Blue Shield), Dental, Vision and company-paid Life Insurance</li>
<li>Company contributions to employee Health Savings Accounts (HSA)</li>
<li>401k Plan with Safe Harbor company-matching</li>
<li>Flexible vacation policy and paid company holidays</li>
<li>Company-provided technology package</li>
<li>Relocation assistance where applicable, including travel and company-provided housing for the first 90 days</li></ul></div></div>

Senior Data Scientist, Customer Data & Marketing

Explore 363+ Analytical data scientist in San Francisco this May. Find roles across top companies and apply now to boost your career.

363 analytical data scientist jobs In San Francisco

Data Scientist, Product Analytics

Data Scientist, Analytics (Technical Leadership)

Data Scientist, Product Analytics

Data Scientist

Advisor - Scientific Data Engineer

Computational Scientist 3 - Cell & Tissue Genomics

Senior Data Scientist, Customer Data & Marketing