data engineer

data scientist

data analyst

advisor - scientific data engineer Jobs in San Francisco

advisor - scientific data engineer

ai engineer, ai & data platforms (aidp) Jobs in San Francisco

ai engineer, ai & data platforms (aidp)

analytical data scientist

Twitch

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

Data Scientist

Asana

<div>
 We're looking for a Staff Data Scientist to help define Asana's growth strategy as users increasingly discover and adopt software through LLM interfaces like ChatGPT, Claude, and Gemini. With millions of knowledge workers now starting their workday in conversational AI tools, we're at an inflection point in how productivity software reaches users. You'll drive Asana's acquisition playbook for the emerging LLM-driven channels and re-imagine new customer onboarding in the AI-era. As part of the PLG organization, you'll leverage data to influence how new users discover, learn about, and decide to start using and paying for Asana.
 
 
 Asana's Data Science team helps us fulfill our mission by informing strategy, defining success metrics, and identifying new ways to deliver user value. Data scientists are at the crux of deepening our understanding of the customers and driving more business outcomes by leveraging experimentation, causal inference, statistical and machine learning techniques, and data storytelling.
 
 
 This role is based in our San Francisco office with an office-centric hybrid schedule. The standard in-office days are Monday, Tuesday, and Thursday. Most Asanas have the option to work from home on Wednesdays. Working from home on Fridays depends on the type of work you do and the teams with which you partner. If you're interviewing for this role, your recruiter will share more about the in-office requirements.
 
 
 
 What you&rsquo;ll achieve:
 
 
 
 <ul>
 <li>
 Work closely with Product Managers and User Researchers (UXR) to understand the needs of our new customers in their first few minutes of interaction with Asana, employing data frameworks and methodologies to understand our user segments, visualize the new user funnel, identify levers for driving conversion revenue, and personalize the onboarding journey to ensure better adoption outcomes.
 </li>
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 Act as the "Data Lead" in a triad with Product and Engineering stakeholders to identify multi-year growth opportunities and prioritize the roadmap.
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 Design experiments that measure product progress, and own key performance metrics.
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 Collaborate and mentor fellow Data Scientists in the team to research, identify and disseminate best practices across teams.
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 Work in a high-performance, dynamic team with a strong focus on velocity and software quality and learn about the upcoming field of AI-Optimization and how LLMs can help boost Asana&rsquo;s value proposition.
 
 
 </li>
 </ul>
 
 About you:
 
 
 
 <ul>
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 5-7 years of data science experience, with majority in growth-focused roles at B2B SaaS companies
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 Proven track record driving acquisition and activation for B2B SaaS products, with specific experience in top-of-funnel growth and new user acquisition.
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 0&rarr;1 builder mentality. You've demonstrated the ability to thrive in highly ambiguous environments where you're inventing new playbooks rather than executing existing ones. You're energized by pioneering work.
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 Experience with AI/ML products, LLM APIs, or third-party platform integrations. Strong preference for candidates who've worked with conversational AI or built features integrating ChatGPT, Claude, or similar platforms.
 </li>
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 Strong analytical foundation with deep fluency in experimentation, A/B testing, and funnel optimization.
 </li>
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 Exceptional cross-functional leadership. You write crisply, tell clear stories, and can influence across product, engineering, design, partnerships, sales, and executive stakeholders. You bring clarity to ambiguity.
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 Strategic business acumen to balance user experience with revenue objectives while translating emerging technology trends into actionable product strategy.
 </li>
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 Genuine AI enthusiasm. You're curious, adaptable, and genuinely excited about how LLMs are transforming software discovery and adoption.
 </li>
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 Expert in relational data modeling and SQL and fluent in at least one modern language useful for data processing (e.g. R, Python, or Scala).
 </li>
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 Familiarity with statistical methods including experimental design, regression, causal inference with observational data and time series modeling.
 </li>
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 Demonstrates curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.
 
 
 </li>
 </ul>
 At Asana, we're committed to building teams that include a variety of backgrounds, perspectives, and skills, as this is critical to helping us achieve our mission. If you're interested in this role and don't meet every listed requirement, we still encourage you to apply.
 
 
 
 What We&rsquo;ll Offer
 
 
 
 Our comprehensive compensation package plays a big part in how we recognize you for the impact you have on our path to achieving our mission. We believe that compensation should be reflective of the value you create relative to the market value of your role. To ensure pay is fair and not impacted by biases, we're committed to looking at market value which is why we check ourselves and conduct a yearly pay equity audit.
 
 
 For this role, the estimated base salary range is between $248,000&ndash;282,000. The actual base salary will vary based on various factors, including market and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base salary range for this role may be modified.
 
 
 In addition to base salary, your compensation package may include additional components such as equity, sales incentive pay (for most sales roles), and benefits. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
 
 
 We strive to provide equitable and competitive benefits packages that support our employees worldwide and include:
 
 
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 Mental health, wellness &amp; fitness benefits
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 Career coaching &amp; support
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 Inclusive family building benefits
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 Long-term savings or retirement plans
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 In-office culinary options to cater to your dietary preferences
 
 
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 </ul>
 These are just some of the benefits we offer, and benefits may vary based on role, country, and local regulations. If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the total compensation and benefits for this role.
 
 
 
 About Us
 
 
 
 Asana is a leading platform for human + AI collaboration. Millions of teams around the world rely on Asana to achieve their most important goals, faster. Asana has been named to Fortune's Best Workplaces for 7+ years and recognized by Fast Company, Forbes, and Gartner for excellence in workplace culture and innovation. We offer an exceptional office-centric culture while adopting the best elements of hybrid models to ensure that every one of our global team members can work together effortlessly. With 13+ offices all over the world, we are always looking for individuals who care about building technology that drives positive change in the world and a culture where everyone feels that they belong.
 
 
 
 Join Asana&rsquo;s Talent Network
 
 to stay up to date on job opportunities and life at Asana.
 
 
</div>

Staff Data Scientist

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 
 
 The Pricing team is a centerpiece of Lyft&rsquo;s marketplace. The Pricing team owns the models and software systems that determine the final prices shown to riders. Working with our business and analytics partners, the team owns tools to ensure Lyft offers competitive prices while making efficient financial trade-offs. Rider Engagement is a fast-growing team within Pricing, focused on developing rider-facing engagement levers and optimizing allocations and decisioning systems to drive both short term and long term business outcomes.
 
 
 As a Data Scientist specializing in Algorithms on the Rider Engagement team, you will develop mathematical models for core discounting systems and address diverse problems across optimization, prediction, machine learning, and inference. You will collaborate with cross-functional teammates and stakeholders to enhance algorithms, build and scale our rider engagement products and systems, and drive business growth. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions and decisioning frameworks. In this role, you will report to a Data Science Manager.
 
 
 
 Responsibilities:
 
 
 
 <ul>
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 Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
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 Prioritize and lead deep dives into our data to uncover new product and business opportunities
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 Be familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
 </li>
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 Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
 </li>
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 Establish metrics that measure the health of our products, as well as rider and driver experience
 </li>
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 Drive collaboration and coordination with cross-functional teams
 </li>
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 Provide coaching and technical guidance for other teammates
 
 
 </li>
 </ul>
 
 Experience:
 
 
 
 <ul>
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 M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
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 2+ years professional experience in a technology company setting
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 Proven experience with building and evaluating machine learning models
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 Proficiency with Python and working in a production coding environment
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 Passion for solving unstructured and non-standard mathematical problems
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 End-to-end experience with data, including querying, aggregation, analysis, and visualization
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 Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem
 
 
 </li>
 </ul>
 
 Benefits:
 
 
 
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 Great medical, dental, and vision insurance options with additional programs available when enrolled
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 Mental health benefits
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 Family building benefits
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 Child care and pet benefits
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 401(k) plan with company match to help save for your future
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 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
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 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
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 Subsidized commuter benefits
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 Monthly Lyft credits and complimentary Lyft Pink membership
 
 
 </li>
 </ul>
 Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
 
 
 Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
 
 
 The expected base pay range for this position in the San Francisco area is $128,000 - $160,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
</div>

Data Scientist - Machine Learning, Pricing & Rider Engagement

OpenAI

<div>
 
 About The Team
 
 
 
 OpenAI&rsquo;s mission is to ensure AGI benefits all of humanity. The API organization is one of the highest-leverage ways we do that: we put frontier intelligence in the hands of builders who turn it into products, businesses, and services that reach people everywhere.
 
 
 We build the infrastructure and developer platform that makes that possible&mdash;so developers can reliably bring powerful AI into the real world, operate it safely at scale, and keep pushing what&rsquo;s possible. When we do our job well, we don&rsquo;t just ship an API. We enable thousands of teams to create new capabilities for millions of end users, accelerating progress across industries and communities.
 
 
 
 About The Role
 
 
 
 As a Data Scientist on the API team, you&rsquo;ll build the measurement systems that make our platform legible and improveable. You&rsquo;ll define the metrics that matter, identify and quantify developer friction, evaluate launches and platform changes, and translate data into product decisions that improve reliability and developer outcomes at scale.
 
 
 You&rsquo;ll partner closely with Product, Engineering, Research, and Finance to ensure our metrics are trusted, our experimentation is rigorous, and our insights turn into shipped improvements.
 
 
 This role is based in San Francisco. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees.
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Own the core KPI framework for the API platform, spanning developer adoption, engagement, retention, and platform health.
 </li>
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 Build end-to-end funnels that identify where developers succeed or get stuck&mdash;from first integration through scaling to production.
 </li>
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 Define and operationalize platform guardrails (e.g., reliability, latency, error rates, cost/efficiency) and connect them to user outcomes.
 </li>
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 Design and evaluate experiments and rollouts to quantify the impact of platform and product changes.
 </li>
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 Partner with product and engineering teams to improve instrumentation, data quality, and metric definitions so decisions are fast and correct.
 </li>
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 Translate complex analysis into clear, actionable insights for leadership and cross-functional stakeholders.
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 Develop and socialize dashboards, tools, and self-serve data products that help teams answer product questions quickly.
 </li>
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 Help establish data science standards and best practices for measuring AI platform performance and developer success.
 </li>
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 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>
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 Expertise in statistics and causal inference, applied in both experimentation and observational studies.
 </li>
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 Expert-level SQL and proficiency in Python for analytics, modeling, and experimentation.
 </li>
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 Proven experience designing and interpreting experiments and making statistically sound recommendations.
 </li>
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 Experience building datasets, metrics, and data pipelines that power production decision-making.
 </li>
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 Experience developing and extracting insights from business intelligence tools (e.g., Tableau) and building self-serve solutions.
 </li>
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 Strong product sense and an impact-driven mindset: you turn ambiguity into crisp frameworks that drive roadmap decisions.
 </li>
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 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>
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 Ability to operate effectively in a fast-moving, ambiguous environment with limited structure.
 </li>
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 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>
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 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

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

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for a Data Scientist to sit at the center of Thrad's decision-making. Every day we serve millions of ad impressions across dozens of publishers and campaigns, and almost every meaningful question at the company (pricing, yield, publisher economics, advertiser performance, category expansion) is a data question. You will own answering them.
This is not a dashboards-on-request role. You will sit inside product and engineering, drive decisions through rigorous causal reasoning, and level up how the whole team thinks about metrics. Your work will directly shape what we build, what we price, and where we grow. You will work closely with our CTO, the founding engineering team, and the commercial team on both internal insight and client-facing reporting.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
Data: ClickHouse for analytics and real-time metrics, PostgreSQL for transactional, Redis for caching</li><li>
Languages: SQL (heavy), Python, notebooks for exploration and production modeling alike</li><li>
Experimentation: in-house A/B testing against live traffic on our publisher network</li><li>
BI and reporting: the team's choice, shipped to both internal stakeholders and Fortune 500 clients</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Build and maintain the analytical infrastructure for ad performance: CTR, CPC, ROAS, CPM, fill rate, yield, across publishers, advertisers, and verticals.</li><li>
Design causal experiments on ad formats, bidding strategies, creative variations, and publisher configurations. Own them from hypothesis to conclusion.</li><li>
Partner with the CRO on pricing experiments, publisher revenue-share modeling, and advertiser performance reviews.</li><li>
Use statistical modeling to turn rich marketplace data into tools that directly shape product decisions: propensity models, yield curves, cohort analyses.</li><li>
Build self-serve dashboards so the rest of the team can answer their own questions against live metrics without a data bottleneck.</li><li>
Own the data model in ClickHouse and the reporting layer feeding both internal dashboards and client-facing performance reports.</li><li>
Help level up the whole team. Encourage data-driven decisions and a deep understanding of the metrics that drive the business forward.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Drive product and commercial decisions using data and causal reasoning, embedded directly in the engineering and go-to-market teams.</li><li>
Design, implement, and execute experiments against live traffic. Analyze results rigorously and kill or scale them fast.</li><li>
Move from a vague business question to a defensible number in a day.</li><li>
Build and maintain the dashboards and reports that both the team and our clients rely on.</li><li>
Collaborate directly with the CTO, co-founders, and commercial team to translate data into action, often within the same day.</li><li>
Contribute to system and schema decisions as we scale from millions to billions of daily ad impressions.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years in data science, analytics engineering, or quantitative analysis. Bonus if you have worked on marketplaces, ads, or other high-velocity data products.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field, or equivalent experience shipping analytical work that drove real decisions.</li><li>
Strong SQL. You can write, optimize, and debug complex queries without reaching for a tool.</li><li>
Solid Python for modeling, analysis, and lightweight production work.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know when to trust a number and when to distrust it.</li><li>
Comfort with experimentation end to end: A/B testing, causal inference, power analysis, sample size calculations, and honest reporting of negative results.</li><li>
Clear written and verbal communication. You can explain a causal finding to an engineer, a founder, and a Fortune 500 client in the same afternoon.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with ClickHouse or other column-oriented OLAP databases at scale.</li><li>
Background in ad tech, programmatic advertising, or two-sided marketplaces.</li><li>
Experience building client-facing dashboards or reporting products used by external customers.</li><li>
Familiarity with dbt, Metabase, Hex, or similar tools.</li><li>
Comfort reading production code to understand where data comes from and where it goes.</li><li>
A relentless focus on continuous learning and the ability to question the status quo when the numbers say you should.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Rich data: A marketplace running at real scale from day one. Your models and experiments have immediate, measurable impact on revenue.</li><li>
Direct impact: Small founding team. Your insights shape pricing, product, and strategy the same week you surface them.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have notebooks, write-ups, experiments, or dashboards you have built that you are proud of, include them. We read every application.</div>

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