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applied scientist

THRAD

<div><h3 class="jobSectionHeader">The Role</h3>
We are looking for an Applied Scientist to own the models that decide which ad appears in which AI conversation, in real time, across millions of queries a day. Ad selection inside LLM chats is a genuinely new problem: no click history, no cookies, no page context. Just an evolving conversation and a few hundred milliseconds to make a decision that has to feel native to the user, relevant to the advertiser, and profitable for the publisher.
This is a research role with a production mandate. Your models go live, not into a paper. You will work directly with our CTO and the founding engineering team on the systems powering millions of ads a day across Fortune 500 campaigns.<h3 class="jobSectionHeader">
Core Tech Stack</h3><ul><li>
ML: PyTorch, embedding-based retrieval, modern transformer architectures</li><li>
Backend: Python (FastAPI), async serving, real-time inference</li><li>
Data: PostgreSQL for transactional, ClickHouse for analytics and event data</li><li>
Infra: AWS, Docker, CI/CD</li><li>
Plus: whatever the problem demands. We pick tools that ship.</li></ul><h3 class="jobSectionHeader">
Example Projects</h3><ul><li>
Design and train contextual ad relevance models for LLM conversations, from retrieval through ranking through creative selection.</li><li>
Build efficient algorithms for real-time bidding and auction mechanics, balancing publisher yield and advertiser ROAS.</li><li>
Productionize regression models to predict downstream conversion from early conversational signals.</li><li>
Apply privacy-preserving clustering methods to categorize conversational context and improve advertiser targeting without compromising user data.</li><li>
Run live experiments against real traffic on our publisher network. Iterate on CTR, ROAS, and conversation quality metrics.</li><li>
Own the evaluation framework for ad quality, relevance, and user experience across the marketplace.</li><li>
Read an ArXiv paper on Monday. Have a prototype running on Friday.</li></ul><h3 class="jobSectionHeader">
What You Will Do</h3><ul><li>
Own the research and shipping of the models powering ad selection across Thrad's network.</li><li>
Move research to production end to end: hypothesis, training, evaluation, deployment, monitoring.</li><li>
Collaborate directly with the CTO and co-founders to translate research direction into working systems, often within the same day.</li><li>
Partner with the Data and Product teams to design and analyze live experiments on real traffic.</li><li>
Contribute to system architecture decisions as we scale from millions to billions of daily ad impressions.</li><li>
Communicate findings clearly to both technical and non-technical audiences across the team.</li></ul><h3 class="jobSectionHeader">
Who You Are</h3>
Must-haves<ul><li>
2 to 5 years of applied ML experience, ideally in ads, search, recommendations, ranking, or NLP.</li><li>
An advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related field &mdash; or equivalent experience shipping production ML.</li><li>
Strong fundamentals in mathematical and statistical modeling. You know why your model works, not just that it does.</li><li>
Fluent in PyTorch, modern transformer architectures, and embedding-based retrieval.</li><li>
Strong Python, comfort with distributed training and inference.</li><li>
You have shipped ML to production at scale. Not just notebooks.</li><li>
You enjoy identifying and owning hard, open-ended problems. You form testable hypotheses and run them to ground.</li><li>
Based in San Francisco or willing to relocate. This is an in-person role at our SF HQ.</li></ul>
Nice-to-haves<ul><li>
Experience with RLHF, preference modeling, or LLM fine-tuning.</li><li>
Background in auction theory, bidding systems, real-time pricing, or yield optimization.</li><li>
Prior work at an ad-tech, search, recommendations, or marketplace company.</li><li>
Published research at NeurIPS, ICML, ACL, KDD, RecSys, or equivalent.</li><li>
Familiarity with ClickHouse or other column-oriented OLAP databases for analytical workloads.</li><li>
A relentless interest in the AI and LLM ecosystem and how advertising will evolve inside conversational interfaces.</li></ul><h3 class="jobSectionHeader">
Why Thrad</h3><ul><li>
First mover: We are defining a new category. Paid ads in AI is an inevitable market and we are building the infrastructure for it.</li><li>
Real traction: Fortune 500 clients, millions of daily impressions, and publisher partners across the AI web, all pre-seed.</li><li>
Research with teeth: Your work ships. Your models run in production against real traffic with real revenue on the line.</li><li>
Direct impact: Small founding team. Your decisions shape the models, the product, and the company.</li><li>
Ownership: Meaningful equity in a company at the intersection of two massive markets: AI and ad tech.</li><li>
Craft: A team that cares about shipping quality, not just quantity.</li></ul><h3 class="jobSectionHeader">
How to Apply</h3>
Send your CV and a brief note on what excites you about building at the intersection of AI and advertising. If you have published work, a GitHub, or models you have shipped that you are proud of, include them. We read every application.</div>

Applied 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

OpenAI

<div>
 
 About The Team
 
 
 
 The Applied team safely brings OpenAI's technology to the world. We released ChatGPT; Plugins; DALL&middot;E; and the APIs for GPT-4, GPT-3, embeddings, and fine-tuning. We also operate inference infrastructure at scale. There's a lot more on the immediate horizon.
 
 
 Our customers build fast-growing businesses around our APIs, which power product features that were never before possible. ChatGPT is a prime example of what is currently possible. We simultaneously ensure that our powerful tools are used responsibly. Safe deployment is more important to us than unfettered growth.
 
 
 The Scaled Abuse team works within our Applied Engineering organization identifying and responding to fraudsters on our platform. We are looking for a data scientist with anti fraud &amp; abuse experience to help architect and build our next-generation anti-abuse systems.
 
 
 
 About The Role
 
 
 
 The Platform Abuse team protects OpenAI&rsquo;s products from abuse. In the data scientist role, you will be responsible for discovering and mitigating new types of misuse, and scaling our detection techniques and processes. Platform Abuse is an especially exciting area since we believe most of the ways our technologies will be abused haven&rsquo;t even been invented yet.
 
 
 
 This role is based in our San Francisco HQ. We offer relocation assistance to new employees.
 
 
 
 
 In This Role, You Will
 
 
 
 <ul>
 <li>
 Design and build systems for fraud detection and remediation while balancing fraud loss, cost of implementation, and customer experience.
 </li>
 <li>
 Work closely with finance, security, product, research, and trust &amp; safety operations to holistically combat fraudulent and abusive actors on our system.
 </li>
 <li>
 Stay abreast of the latest techniques and tools to stay several steps ahead of determined and well resourced adversaries.
 </li>
 <li>
 Utilize GPT-5 and future models to more effectively combat fraud and abuse.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You
 
 
 
 <ul>
 <li>
 Have experience on a highly technical trust and safety team and/or have worked closely with policy, content moderation, or security teams.
 </li>
 <li>
 Can use coding languages (Python preferred) to programmatically explore large datasets and generate actionable insights to solve problems.
 </li>
 <li>
 Proven ability to propose, design, and run rigorous experiments (A/B tests, quasi-experiments, simulations) with clear insights and actionable product recommendations, leveraging SQL and Python.
 </li>
 <li>
 Excellent communication skills with a track record of influencing cross-functional partners, including product managers, engineers, policy leads, and executives.
 </li>
 <li>
 Bonus if you have experience with deploying scaled detection solutions using large language models, embeddings, or fine tuning.
 </li>
 <li>
 5+ years of quantitative experience in ambiguous environments, ideally as a data scientist at a hyper-growth company or research org, with exposure to fraud, abuse, or security problems.
 
 
 </li>
 </ul>
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
</div>

Data Scientist, Integrity

Cribl

<div><div>Join the company that's building the telemetry infrastructure for the AI era. At Cribl, we partner with IT and Security teams at many of the world's biggest enterprises, including half of the Fortune 100, to bridge the gap between AI ambition and infrastructure reality. As the AI Platform for Telemetry, we give customers the choice, control, and flexibility to manage and analyze telemetry for both humans and agents, so they can build what's next.

We're one of the fastest‑growing private companies and a leading player in a massive, fast‑moving market. With a global workforce, we're remote‑first and grounded in a simple idea: software is a people business. Cribl is the place where curious, collaborative people can do their best work, grow fast, and bring their full selves to the herd.</div>
Why You'll Love This Role

Cribl is hiring a Senior Data Scientist to join and grow our internal data science practice. In this role, you'll use predictive models and advanced analytics to give stakeholders clear foresight into what's likely to happen and what to do next. This role is embedded in our centralized data organization, reporting to our Staff Data Scientist, partnering closely with teams like Finance, GTM, and People. You'll turn rich data sets into forward-looking insights that guide planning, business strategy, and execution, and you'll contribute to the technical standards and culture that make our &quot;Foresight First&quot; vision a reality.

We pride ourselves on fostering a collaborative and innovative culture where team members enjoy working together - whether remotely or over a meal at a foodie hot spot. If you're someone who thrives in an entrepreneurial environment and is eager to contribute to a company poised for legendary success in the tech industry, we want to hear from you! 

As An Active Member Of Our Team, You Will&hellip;
<ul>
<li>Own end-to-end data science initiatives that translate ambiguous business questions into clear analytical and modeling problems, from scoping through implementation.</li>
<li>Build, operationalize, and continuously improve machine learning models in partnership with Data Engineering to ensure scalable training &amp; evaluation workflows in production.</li>
<li>Evaluate and interpret the performance of ML models (e.g., classification, recommendation), helping the team reason through trade-offs, limitations, and business implications of model-driven decisions.</li>
<li>Conduct deep-dive analyses using advanced statistical methods to surface actionable insights to stakeholders and positively influence org-wide decision quality.</li>
<li>Apply statistical modeling, experimentation, and AI-assisted analytics to expand how Cribl uses data to answer challenging questions.</li>
<li>Communicate findings clearly and persuasively to executives and cross-functional stakeholders to influence strategic decision-making.</li>
<li>Contribute to technical best practices and team standards, and provide mentorship to junior team members as the practice grows.</li>
<li>Partner closely with Data Engineering, Analytics, and Governance to define data requirements, improve data quality, and ensure the team can efficiently generate trustworthy insights.</li>
<li>We are a remote-first company and work happens across many time-zones &ndash; you may be required to occasionally perform duties outside your standard working hours.</li></ul> 
 
If You've Got It - We Want It
<ul>
<li>5+ years of experience in data science or applied statistics with a track record of driving data science projects with meaningful business impact at a software company.</li>
<li>Strong background in experiment design, causal inference, predictive modeling, and ability to distinguish signal vs noise.</li>
<li>Advanced SQL and Python skills, with experience working on large, messy, multi-source datasets within a modern data stack such as cloud data warehouses and transformation frameworks.</li>
<li>Proven ownership of end-to-end data science and ML solutions, from problem framing and data preparation through modeling, validation, deployment to production in partnership with Data Engineering, and ongoing monitoring.</li>
<li>Ability to work effectively in ambiguous, fast-changing environments, navigating from problem framing through implementation and iteration.</li>
<li>Excellent communication, including the ability to present complex findings to non-technical audiences and contribute to strategic decisions</li>
<li>Familiarity with AI-assisted workflows, including leveraging LLMs as tools to accelerate analysis, surface insights, or augment modeling work.</li></ul> 
 
Salary Range ($120,000 - $175,000)

The salary for this role is dependent on geographic location. The salary offered within the range described will be based on the individual candidate's job-related knowledge, skills, and experience. In addition to a competitive salary, Cribl also offers a generous benefits package which includes health, dental, vision, short-term disability, and life insurance, paid holidays and paid time off, a fertility treatment benefit, 401(k), equity, and eligibility for a discretionary company-wide bonus. 
 
#LI-JB1 
#LI-Remote<div>
Bring Your Whole Self 
 
Diversity drives innovation, enables better decisions to support our customers, and inspires change for the better. We're building a culture where differences are valued and welcomed, and we work together to bring out the best in each other. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.

Interested in joining the Cribl herd? Learn more about the smartest, funniest, most passionate goats you'll ever meet at cribl.io/about-us.</div></div>

Senior Data Scientist

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

Prolific

<div>
 
 AI Trainer &ndash; Research Scientists
 
 
 
 
 
 About Prolific
 
 
 
 
 Prolific is not just another player in the AI space &ndash; we are building the biggest pool of quality human data in the world.
 
 
 Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.
 
 
 
 
 The role
 
 
 
 
 We&rsquo;re looking for people with Research Scientist experience to work as self-employed AI Trainers to help train and evaluate cutting-edge AI models from some of the world&rsquo;s biggest AI labs. If you have the necessary experience, we&rsquo;ll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you&rsquo;ll be invited to join Prolific as a Domain Expert participant, where you&rsquo;ll get paid to train and evaluate powerful AI models.
 
 
 Researchers looking for your skills tend to pay up to $50/hr subject to the length of tasks available. If successful, you must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.
 
 
 
 
 What you&rsquo;ll be doing in the role
 
 
 
 
 Completing AI training tasks such as analyzing, editing, and writing research-focused content
 
 
 Judging the performance of AI on research design, methodology, and scientific reasoning prompts
 
 
 Improving cutting-edge AI models using your experience in research and experimentation
 
 
 
 
 What you&rsquo;ll bring
 
 
 
 
 Experience working as a Research Scientist or in a closely related research role
 
 
 A strong understanding of scientific methodology, experimental design, and data analysis
 
 
 A willingness to take our skills verification test to assess your suitability for our Domain Expert participant pool
 
 
 Strong attention to detail and the ability to concentrate on complex tasks for up to one hour at a time
 
 
 A reliable and fast internet connection and access to a computer
 
 
 A Paypal account to receive payment from our clients*
 
 
 
 
 Why Prolific is a great platform to join as a Domain Expert participant
 
 
 
 
 Joining our platform as a Prolific participant will give you the chance to influence the AI models of the future. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.
 
 
 We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.
 
 
 We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation &ndash; one that reflects the breadth and the best of humanity.
 
 
 <ul>
 <li>
 Participants are self-employed and need to declare earnings to their respective tax authorities. Prolific has no liability for any tax obligations or reporting requirements resulting from compensation received through this platform. Each participant is solely responsible for compliance with applicable tax laws in their jurisdiction.
 
 
 </li>
 </ul>
 
 Links to more information on Prolific
 
 
 
 Website
 
 
 Youtube
 
 
 Privacy Statement
 
 
 By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal information.
</div>

AI Training - Research Scientist (PST)

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

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