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machine learning scientist

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
We are seeking a Senior Applied Scientist to build production machine learning systems that solve complex business problems at scale. You will design, develop, and deploy ML solutions that directly impact millions of users and drive strategic decision-making across the organization. 
 
In this role, you will work on challenging problems spanning predictive modeling, natural language processing, recommendation systems, and generative AI applications. You will collaborate with cross-functional teams to translate ambiguous business challenges into rigorous technical solutions. 
 
Key job responsibilities 
<ul><li>Design and deploy large-scale machine learning systems in production environments</li><li>Develop innovative ML solutions using state-of-the-art techniques including deep learning, NLP, and generative AI</li><li>Create ML solutions that standardize and optimize manager-employee interactions, providing intelligent suggestions and establishing metrics to measure engagement quality across diverse conversation types</li><li>Partner to build causal inference models and experimental frameworks to measure impact</li><li>Collaborate with product managers, engineers, and business leaders to define technical roadmaps</li><li>Communicate complex technical concepts to diverse audiences, from technical peers to senior leadership</li></ul> 
About the team 
The People eXperience and Technology Central Science Team (PXTCS) uses economics, behavioral science, statistics, and machine learning to proactively identify mechanisms and process improvements which simultaneously improve Amazon and the lives, wellbeing, and the value of work to Amazonians. We are an interdisciplinary team that combines the talents of science and engineering to develop and deliver solutions that measurably achieve this goal.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 5+ years of applied research experience</li><li>3+ years of building machine learning models for business application 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 large scale distributed systems such as Hadoop, Spark etc.</li><li>Proven track record of leading end-to-end development from Ideation to monitoring in production</li><li>Proven track record of mentoring and growing junior and mid-level scientists</li><li>Experience with building LLMs, generative AI applications on AWS</li><li>Excellent communication skills with ability to influence senior leadership</li><li>Demonstrated ability to work in ambiguous problem spaces with evolving requirements</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, MA, Boston - 167,100.00 - 226,100.00 USD annually 
USA, VA, Arlington - 167,100.00 - 226,100.00 USD annually 
USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Senior Applied Scientist, PXT Central Science

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 Central Market Management &amp; AI (CMM&amp;AI) team, a key part of the broader Rideshare Experience &amp; Marketplace organization, is essential for maintaining a balanced and efficient marketplace. We do so by developing foundational models, business datasets, and decision-making applications that support a wide range of teams across Lyft. These critical platforms and tools power our pricing / pay strategy, operational alignment, and regional strategies, enabling us to compete effectively in the Rideshare landscape.
 
 
 Data Scientists in CMM&amp;AI solve the foundational problems that drive Lyft&rsquo;s marketplace. From forecasting supply and demand to optimizing investments and measuring the ROI of growth levers, our work shapes both automated processes and high-level strategic decisions. Because our challenges are unique to a real-time marketplace, we avoid off-the-shelf solutions in favor of creativity and first-principles mathematical reasoning. We leverage a deep stack of technologies across forecasting, machine learning, inference, and optimization to deliver measurable impact.
 
 
 As a Senior Data Scientist on the Foundational Models team in CMM&amp;AI, you will operate at the intersection of Machine Learning, Data Science, and Economics to build scalable optimization and modeling systems that directly impact Lyft&rsquo;s top and bottom lines. You will be hands-on with formulating optimization problems, building ML models, productionizing pipelines, and integrating their outputs within decision-making frameworks. You will collaborate with Product, Engineers, Data Scientists, and Analysts to help define the roadmap and architecture for our next generation of foundational marketplace models that accelerate iterations and drive business efficiency.
 
 
 Responsibilities:
 
 
 <ul>
 <li>
 Optimization &amp; Modeling
 </li>
 <ul>
 <li>
 Design, formulate, and solve complex mathematical optimization problems that power Lyft&rsquo;s marketplace decisions across pricing, pay, incentives, and resource allocation.
 </li>
 <li>
 Build, deploy, and maintain production-grade ML and optimization models; collaborate with Software Engineering to integrate algorithms into live systems and establish robust monitoring for model performance and data health.
 </li>
 <li>
 Own the full model lifecycle&mdash;from problem framing and prototyping through experimental validation and production deployment&mdash;refusing a &ldquo;build and forget&rdquo; mentality.
 </li>
 <li>
 Apply first-principles mathematical reasoning to marketplace challenges, choosing the simplest effective solution and building complexity only when incremental value justifies the technical debt.
 </li>
 </ul>
 <li>
 Technical Strategy &amp; Execution
 </li>
 <ul>
 <li>
 Drive large-scale technical projects from initial concept to high-impact execution, ensuring alignment with business priorities and Lyft&rsquo;s overarching goals.
 </li>
 <li>
 Contribute to and influence the multi-quarter technical roadmap for foundational models, helping shape the vision and architecture for next-generation optimization and forecasting systems.
 </li>
 <li>
 Champion high standards for code quality through well-tested, maintainable code and the development of shared team components and libraries.
 </li>
 <li>
 Infuse AI capabilities into existing workflows and demonstrate agility in adopting emerging AI models and techniques to keep Lyft at the forefront of marketplace optimization.
 </li>
 </ul>
 <li>
 Stakeholder Partnership &amp; Influence
 </li>
 <ul>
 <li>
 Partner with Data Scientists, Engineers, Product Managers, and Business Partners across lever teams (Pricing, Pay, Driver Engagement, Rider Engagement) to frame problems mathematically and within the business context.
 </li>
 <li>
 Serve as a subject matter expert on optimization and modeling, providing technical guidance and thought leadership to elevate the team&rsquo;s capabilities.
 </li>
 <li>
 Foster a data-driven culture by presenting actionable insights and recommendations to senior leadership and cross-functional stakeholders.
 </li>
 <li>
 Influence stakeholder roadmaps and advise cross-functional partners on the long-term trade-offs of different algorithmic approaches.
 
 </li>
 </ul>
 </ul>
 Experience:
 
 
 <ul>
 <li>
 Required:
 </li>
 <ul>
 <li>
 M.S. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
 </li>
 <li>
 4+ years of hands-on experience developing and deploying optimization and/or machine learning models in a production environment.
 </li>
 <li>
 Advanced proficiency in Python and SQL, with a focus on writing clean, maintainable, and well-tested production code.
 </li>
 <li>
 End-to-end experience with data, including querying, aggregation, analysis, and visualization.
 </li>
 <li>
 Passion for solving unstructured and non-standard mathematical problems using first-principles reasoning.
 </li>
 <li>
 Excellent communication skills and a track record of working closely with Software Engineers, Analysts, and Business Stakeholders to drive decision-making.
 </li>
 </ul>
 <li>
 Preferred:
 </li>
 <ul>
 <li>
 Ph.D. in Operations Research, Industrial Engineering, Mathematics, Computer Science, Statistics, Economics, or other quantitative fields.
 </li>
 <li>
 Experience in pricing optimization, marketplace design, and/or resource allocation in a two-sided marketplace environment.
 </li>
 <li>
 Proven track record of delivering measurable business value through the full lifecycle of model development, including experimental design and causal inference.
 </li>
 <li>
 Deep understanding of how various levers (e.g., pricing, incentives, supply positioning) influence marketplace equilibrium and system-wide dynamics.
 </li>
 <li>
 Experience with productionizing algorithms for real-time or near-real-time decision systems.
 </li>
 <li>
 Experience influencing technical roadmaps and advising cross-functional partners on the long-term trade-offs of different algorithmic approaches.
 </li>
 <li>
 Exposure to modern AI/ML frameworks or integration patterns
 
 </li>
 </ul>
 </ul>
 
 Benefits:
 
 
 
 <ul>
 <li>
 Great medical, dental, and vision insurance options with additional programs available when enrolled
 </li>
 <li>
 Mental health benefits
 </li>
 <li>
 Family building benefits
 </li>
 <li>
 Child care and pet benefits
 </li>
 <li>
 401(k) plan with company match to help save for your future
 </li>
 <li>
 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
 </li>
 <li>
 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
 </li>
 <li>
 Subsidized commuter benefits
 </li>
 <li>
 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 $148,000 - $185,000, 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>

Senior Data Scientist - Optimization, Central Market Management & AI

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

Google

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field, or equivalent practical experience.</li>
<li>5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis, or 3 years of experience with a PhD degree.</li>
<li>4 years of experience in data analysis or related fields as a statistician or data scientist.</li>
<li>Experience with statistical software (e.g., R, Python, MATLAB, pandas) and database languages (e.g., SQL).</li>
<li>Experience with statistical methodologies.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>PhD degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.</li>
<li>8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. 
</li>
<li>Experience in training, validating or optimizing language models or LLM-based classifiers.</li>
<li>Experience analyzing multi-modal data (image, audio, or video).</li>
<li>Experience of GenAI safety and red-teaming.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
User Protection is an organization dedicated to protecting Google's users from abuse, account compromise and other harms online. Our team works with the Content Safety (CS) and User Protection Platform and Services (UPS) which develops tools to protect users from abusive content at scale, often leveraging AI technology to do so. Our team provides data science capabilities to these two organizations, and works directly with product and engineering to evaluate, understand, and improve the quality of our protections. Organizationally, we are a part of a large data science team in Core, which provides ample opportunities for knowledge sharing, development, and learning from other data scientists working in adjacent domains. 
 
CS and UPS equip Google products with tools to protect users from abuse and harm. As a Data Scientist working with CS and UPS, you'll be helping to evaluate, understand, and improve our abuse protections - which are generally built with and for AI tools. We work closely with cross-functional product teams on specific content safety classifiers, but also on generic strategies and tooling for understanding content safety classifiers. 
 
Our team is designing safety data evaluations and safety mitigation evaluations, including LLM-as-judge, prompt injection, and Responsible AI testing. We also work with flagship GenAI product teams on understanding Google-wide GenAI safety postures in production traffic.The US base salary range for this full-time position is $174,000-$252,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.<div></div><div> 
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div></div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Solve ambiguous problems in the Generative Artificial Intelligence safety space, including agent-based safety. 
</li>
<li>Develop quantitative methodologies to curate training data and evaluation data from synthetic data and real-world production data for improving content safety mitigations. Design and evaluate models to mathematically express and solve defined problems with limited precedent.</li>
<li>Drive cross-functional alignment on measuring violation rates and unjustified refusals across multiple flagship Generative Artificial Intelligence product surfaces. Identify and clarify business or product questions.</li>
<li>Provide feedback and refine business questions into tractable analysis, evaluation metrics, or mathematical models. Drive clarity and coherence in understanding safety at scale across Google.</li>
<li><div>Own the process of gathering, extracting, and compiling data across sources (e.g., SQL, R, Python). Format, re-structure, or validate data to ensure quality, and review the dataset to ensure it is ready for analysis.</div></li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Senior Research Data Scientist, Core Safety Data Science

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

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About The Role
 
 
 
 Untangling the science of Data &amp; Evaluations for Frontier AI
 
 
 Thanks to our massive network of the world&rsquo;s top experts in all domains, the demand for human data from Handshake AI has exploded (with revenue growing from 0 to well over 9-figures in the first year and growth only accelerating since). Now the world&rsquo;s top AI Labs are looking to Handshake for advice on how to leverage human expertise to make frontier models more useful for everyone, and we are forming a leading research group to advance the science of Data and Evaluations for AI.
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Publish papers, open source software, and do bleeding-edge open science on AI agents, LLMs and frontier multimodal models, RL environments, post-training.
 </li>
 <li>
 Work with all of the top AI Labs in the world and understand/shape what their researchers are prioritizing (uniquely, you get to work on research at a company whose customers are top AI researchers)
 </li>
 <li>
 Create public benchmarks that meaningfully measure AI progress, leveraging thousands of the world&rsquo;s top experts in different domains from the Handshake network to construct the most representative/high-quality benchmark.
 </li>
 <li>
 Shape the frontier of AI through high-impact research on topics that matter: how to measure/value data, how to effectively evaluate AI, what shapes of data are most effective as AI advances, what makes effective training/RL environments, post-training data recipes.
 
 
 </li>
 </ul>
 
 Desired Capabilities
 
 
 
 <ul>
 <li>
 Based in San Francisco, and excited to work in the office.
 </li>
 <li>
 Ph.D. in ML/AI, data science, or related fields.
 </li>
 <li>
 Publications in top AI/ML venues like NeurIPS, ICML, ICLR.
 </li>
 <li>
 Builders who love to tinker with LLMs/Agents and ship high-quality software, benchmarks/datasets, research, blogs.
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 
 
 The below benefits are for full-time US employees.
 
 
 
 
 🎯
 
 Ownership:
 
 Equity in a fast-growing company
 
 
 💰
 
 Financial Wellness
 
 : 401(k) match, competitive compensation, financial coaching
 
 
 🍼
 
 Family Support:
 
 Paid parental leave, fertility benefits, parental coaching
 
 
 💝
 
 Wellbeing:
 
 Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚
 
 Growth:
 
 $2,000 learning stipend, ongoing development
 
 
 💻
 
 Remote &amp; Office:
 
 Internet, commuting, and free lunch/gym in our SF office
 
 
 🏝
 
 Time Off:
 
 Flexible PTO, 15 holidays + 2 flex days, winter #ShakeBreak where our whole office closes for a week!
 
 
 🤝
 
 Connection:
 
 Team outings &amp; referral bonuses
 
 
 Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
 
 
 Compensation Range: $320K - $365K
 
 
</div>

AI Research Scientist

PRAVAH

<div>About Pravāh
Pravāh is building foundational intelligence for the electric grid. We are a team of researchers and engineers who met at Stanford. We use machine learning to help electric utilities make real-time decisions on grid planning and operations to reduce blackout risks and reduce volatility caused by extreme events.
We are backed by Khosla Ventures, Pear VC, and Conviction.
To know more about who we are, what we are building, and why we are excited read this Notion! https://pravah.notion.site/ 
The Role
We do not have a predefined job description for this posting, and that is intentional.
If you have come across what we are building and thought &quot;I know exactly how I could contribute, but I do not see a role for it,&quot; this is for you. We are open to exceptional people across machine learning, software engineering, power systems, weather, business development, operations, and domains we have not even thought of yet.
We are a small team solving genuinely hard problems at the frontier of AI and physical infrastructure. The right person for this role will come in with a point of view: a clear sense of what they are great at, where they see a gap at Pravāh, and how they would fill it. We will figure out the rest together. 
What You Might Work On
This depends entirely on you and what you bring. Past examples of roles candidates have proposed, or that we could imagine:<ul><li>
A machine learning researcher who wants to define a new modeling direction in GNNs, RL, or computer vision</li><li>
A power systems engineer who wants to bridge grid physics and our AI stack</li><li>
A forward deployed engineer who understands utility operations and wants to own technical deployments end-to-end</li><li>
A founding engineer who wants to own our product deployment</li><li>
A weather scientist who sees an opportunity to push the frontier of AI-weather prediction for grid applications</li><li>
A GTM or BD specialist who knows the utility landscape and wants to build our commercial motion 
</li></ul> 
What we always look for<ul><li>
High agency and a bias for action. You build, fix, and ship. You do not wait for perfect conditions or a detailed playbook.</li><li>
Full ownership from Day 1. You thrive in ambiguity, reason from first principles, and take problems end-to-end.</li><li>
High standards. We are building the core decision engine for the modern grid, not optimising for a local maximum. We want people who think the same way.</li><li>
Easy to work with. We hugely value people who are relaxed and friendly while also being intense and absolute hustlers. Our lives are crazy and only getting crazier, in the best way possible.</li><li>
Strategic thinking. How do we accomplish 10x what we are doing today? We want people who hold the long-term roadmap and the short-term execution in their heads at the same time.</li></ul>
What You Will Gain<ul><li>
The chance to work on hard, open-ended problems at the intersection of AI and physical infrastructure.</li><li>
Ability to shape technical direction at a company that is early enough for your ideas to genuinely change the trajectory.</li><li>
Close collaboration with a deeply technical and motivated founding team.</li></ul>
Compensation Range: $150K - $250K</div>

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