data scientist

Triumph

<div>
 
 The Role
 
 
 
 As a Data Scientist, you'll own the quantitative systems that drive how millions of real-money players experience Triumph's products, from their first session to long-term retention and monetization. You'll build the models and frameworks behind our most critical business decisions: how we price, how we pay out, how we match players, and how we grow.
 
 
 You'd be joining a small, high-output quant team (4 people today) that operates like a trading desk. We build the mathematical systems that power Triumph's core business: pricing engines, payout distributions, matchmaking algorithms, risk models, and player behavior systems. Every model we ship touches real money and real users. You see the impact in the numbers the next day.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Monetization &amp; Pricing: Develop and optimize the pricing engines, payout structures, and edge calculations that are the mathematical backbone of Triumph's revenue. Own pack economics, rarity calibration, and pricing models for Rips by Triumph.
 </li>
 <li>
 User Journey &amp; Retention: Build models that map the full player lifecycle: acquisition, activation, engagement, monetization, churn risk. Identify the quantitative levers that move retention and LTV, and design interventions that act on them.
 </li>
 <li>
 Experimentation: Design and analyze experiments (A/B tests and beyond) with rigorous statistical methodology. Own the measurement framework that tells us what's actually working across the product.
 </li>
 <li>
 Behavioral Modeling: Develop ML and statistical models on rich, high-frequency user behavior data (session patterns, spend curves, matchmaking outcomes, gameplay trajectories) to drive both product decisions and real-time production systems.
 </li>
 <li>
 Growth &amp; Acquisition: Build models that directly inform acquisition spend and channel optimization, connecting upstream marketing decisions to downstream LTV and monetization outcomes.
 </li>
 <li>
 Cross-Functional Impact: Partner closely with engineering, product, and leadership to translate model outputs into shipped features and strategic decisions. Identify high-leverage quantitative problems across the business and drive them from formulation to production impact.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Bachelor's degree in a quantitative subject: math, physics, computer science, statistics, economics, or a related discipline.
 </li>
 <li>
 True depth and mastery in at least one quantitative domain: probability, statistics, applied ML, causal inference, or mathematics. We want spiky people who are confident they are among the best in their discipline.
 </li>
 <li>
 Proficiency in Python and SQL.
 </li>
 <li>
 Experience working with large-scale user or behavioral datasets.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in consumer tech, gaming, fintech, or marketplace data science, particularly in monetization, LTV modeling, or experimentation.
 </li>
 <li>
 Prior experience as a quantitative trader or quantitative researcher.
 </li>
 <li>
 Experience in competitive math, physics, or CS olympiads, or a graduate degree in a quantitative discipline.
 </li>
 <li>
 Nationally competitive in any activity. Some members of our team include national champions in debate, Clash Royale, and Poker.
 
 
 </li>
 </ul>
 
 Why Triumph?
 
 
 
 <ul>
 <li>
 High growth. Build a high-scale consumer platform that touches gaming, finance, and social with the autonomy to set our web direction.
 </li>
 <li>
 High agency. Small, high-impact engineering team that is growing rapidly with significant opportunity for leadership and growth.
 </li>
 <li>
 High energy. Passionate team who are proud of our work and velocity (16x year over year growth).
 </li>
 <li>
 Competitive salary and benefits. $400/mo lunch credit, healthcare, vision, dental, 401k, etc.
 
 
 </li>
 </ul>
 Our team gathers 5 days a week at Triumph&rsquo;s headquarters at Levi&rsquo;s Plaza in San Francisco.
 
 
 Compensation Range: $200K - $400K
 
 
</div>

Data Scientist

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>

Turo

<div>
 
 About The Team
 
 
 
 You are a creative and rigorous data scientist with 2+ years of experience, excited to solve meaningful business problems. You are comfortable with a range of statistical and machine learning techniques with the ability to creatively apply them to our problems. Modeling is your thing, you are proficient in translating unstructured business problems into mathematical frameworks, and propose scalable solutions.
 
 
 You have a passion for consumer products, shipping code, and data focused experiments. You are excited to play a key role in crafting the product from inception to implementation and beyond.
 
 
 
 What You Will Do
 
 
 
 <ul>
 <li>
 Work closely with engineers, product managers and other data scientists to develop algorithms and drive key product and modeling decisions.
 </li>
 <li>
 Lead the end-to-end process of conceptualizing, developing, deploying, and analyzing models.
 </li>
 <li>
 Present your insights and suggestions to audiences of all levels in the company.
 </li>
 <li>
 Dedicatedly perform explorations of data and algorithms to improve our models.
 </li>
 <li>
 Own the data quality of your projects including training, test and experiment data.
 </li>
 <li>
 Research the best metrics; design and validate experiments to measure model performance.
 
 
 </li>
 </ul>
 
 Your Profile
 
 
 
 <ul>
 <li>
 Deep understanding of mathematical methods in statistics, optimization, and machine learning. Demonstrable experience applying these methods to real world prediction problems (classification, regression, recommendation systems, time series).
 </li>
 <li>
 Strongly self-motivated with a keen eye for detail. A natural desire to learn and innovate with like-minded colleagues.
 </li>
 <li>
 Fluent in a production-ready programming language such as Python. Ability to deploy and scale models into a production environment collaborating with engineers.
 </li>
 <li>
 Fluent in common data science tools (e.g. scikit-learn, numpy, pandas) in Python/R (preferred).
 </li>
 <li>
 Fluent in SQL, ability to efficiently query large datasets.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience in experiment design and analysis.
 </li>
 <li>
 Experience with AWS data warehouses and services,
 </li>
 <li>
 Experience with Airflow.
 
 
 </li>
 </ul>
 The SF base salary target range for this full-time position is $134,000-$168,000 + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position in San Francisco, CA. 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 work location during the hiring process.
 
 
 
 Turo 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; Turists will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Turo 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 Turo offers.
 
 
 
 
 Turo AI Policy
 
 
 
 Turo may use AI-enabled tools to support our recruiting operations, including gathering information from candidates, drafting communications, helping with interview note-taking and assessment, and so on. These tools only supplement our team; all decisions to advance or hire candidates are made by Turo employees. While we welcome candidates to use AI-enabled tools to help prepare for their interviews, the use of such tools, including any AI chatbots or note-takers, is not permitted during live interviews or technical assessments. We want to see how you consider and solve problems in real-time, so interviews and assessments are all you (unless we indicate otherwise and ask you specifically to use an AI-enabled tool to answer a question). If during the application process you require the use of an AI-enabled tool as a reasonable accommodation for a disability, please let us know at PeopleOps@turo.com.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 Competitive salary, equity, benefits, and perks for all full-time employees
 </li>
 <li>
 Employer-paid medical, dental, and vision insurance (Country specific)
 </li>
 <li>
 Retirement employer match
 </li>
 <li>
 Learning &amp; Development stipend to invest in your professional development
 </li>
 <li>
 Turo host matching program
 </li>
 <li>
 Turo travel credit
 </li>
 <li>
 Cell phone and internet stipend
 </li>
 <li>
 Paid time off to relax and recharge
 </li>
 <li>
 Paid holidays, volunteer time off, and parental leave
 </li>
 <li>
 For those who are in the office full-time or hybrid we have in-office lunch, office snacks, and fun activities
 
 
 </li>
 </ul>
 We are committed to building a diverse team. If you are from a background that's underrepresented in tech, we'd love to meet you.
 
 
 Aside from an award winning work environment and the opportunity to be part of the world&rsquo;s largest car sharing marketplace, we are also growing the team quickly - join us! Even if you don't meet every qualification, we are looking for people with enthusiasm for what we do and we will consider you for this and other possibilities.
 
 
 
 About Turo
 
 
 
 Turo is the world&rsquo;s largest car sharing marketplace where you can book the perfect car for wherever you&rsquo;re going from a vibrant community of trusted hosts across the US, UK, Canada, Australia, and France. Whether you're flying in from afar or looking for a car down the street, searching for a rugged truck or something smooth and swanky, Turo puts you in the driver's seat of an extraordinary selection of cars shared by local hosts.
 
 
 Discover Turo at https://turo.com, the App Store, and Google Play, and check out our blog, Field Notes.
 
 
 Read more about the Turo culture according to Turo CEO, Andre Haddad.
 
 
 Turo is an Equal Opportunity Employer and a participant in the U.S. Federal E-Verify program. Women, minorities, individuals with disabilities and protected veterans are encouraged to apply. We welcome people of different backgrounds, experiences, abilities and perspectives.
 
 
 Turo will consider qualified applicants with criminal histories in a manner consistent with the San Francisco Fair Chance Ordinance, as applicable.
 
 
 We welcome candidates with physical, mental, and/or neurological disabilities. If you require assistance applying for an open position, or need accommodation during the recruiting process due to a disability, please submit a request to People Operations by emailing PeopleOps@turo.com.
 
 
</div>

OpenAI

<div>
 
 About The Team
 
 
 
 The Preparedness team is an important part of the Safety Systems org at OpenAI, and is guided by OpenAI&rsquo;s Preparedness Framework.
 
 
 Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models.
 
 
 
 The Mission Of The Preparedness Team Is To
 
 
 
 <ul>
 <li>
 Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society
 </li>
 <li>
 Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems
 
 
 </li>
 </ul>
 Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society.
 
 
 
 About The Role
 
 
 
 We&rsquo;re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes.
 
 
 This position goes beyond &ldquo;running evals.&rdquo; You&rsquo;ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm).
 
 
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas).
 </li>
 <li>
 Diagnose false positives and false negatives with deep error analysis, root cause investigation, and clear recommendations for mitigation adjustments.
 </li>
 <li>
 Build monitoring and measurement frameworks to track mitigation effectiveness over time and across user segments and use cases.
 </li>
 <li>
 Identify trends in over-blocking vs. under-blocking, quantify customer impact, and propose prioritized interventions.
 </li>
 <li>
 Develop insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes.
 </li>
 <li>
 Expand risk monitoring into new areas, including cybersecurity threats and model loss-of-control or sabotage scenarios, in partnership with domain experts.
 </li>
 <li>
 Communicate results to technical and executive stakeholders with crisp narratives, decision-ready metrics, and clear tradeoffs.
 
 
 </li>
 </ul>
 
 You Might Thrive In This Role If You Are
 
 
 
 <ul>
 <li>
 An autonomous operator: you can take a problem statement and independently structure the analysis end-to-end.
 </li>
 <li>
 Strong at executive-ready communication: concise, clear, and outcome-oriented.
 </li>
 <li>
 Skilled in turning analysis into productable changes: you&rsquo;re comfortable influencing across functions to drive mitigation improvements.
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Significant experience in data science or applied analytics in high-stakes domains (e.g., security, trust &amp; safety, abuse prevention, fraud, platform integrity, or reliability).
 </li>
 <li>
 Strong foundations in experimentation, causal thinking, and/or observational inference; ability to design robust measurement under imperfect data.
 </li>
 <li>
 Fluency in SQL and Python (or equivalent) for analysis, modeling, and building monitoring workflows.
 </li>
 <li>
 Experience building metrics, dashboards, and operational monitoring that meaningfully changes outcomes (not just reporting).
 </li>
 <li>
 Track record of driving cross-functional impact with engineering, product, and research partners.
 </li>
 <li>
 Cybersecurity data science experience (strong preference), including exposure to threat modeling, adversarial dynamics, abuse patterns, or security telemetry.
 </li>
 <li>
 Experience with classifier evaluation, calibration, thresholding, and error analysis at scale. Familiarity with detection systems in adversarial settings (e.g., evasion, distribution shift, feedback loops).
 </li>
 <li>
 Trust &amp; Safety experience is helpful, but not required.
 </li>
 <li>
 Genuine interest in AI safety, alignment, and catastrophic risk prevention.
 
 
 </li>
 </ul>
 
 About OpenAI
 
 
 
 OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.
 
 
 We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
 
 
 For additional information, please see OpenAI&rsquo;s Affirmative Action and Equal Employment Opportunity Policy Statement.
 
 
 Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
 
 
 To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
 
 
 We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
 
 
 OpenAI Global Applicant Privacy Policy
 
 
 At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.
 
 
 Compensation Range: $347K - $400K
</div>

Data Scientist, Preparedness

Tacit

<div>
 
 About Tacit
 
 
 
 We are an early-stage, deep tech startup based in San Francisco, developing innovative hardware that rethinks human-computer interaction. We are backed by General Catalyst, Khosla Ventures, and Greylock Partners, with a founding team from Stanford, BrainGate, Oculus, and Tesla. While we can&rsquo;t reveal too much just yet, our team is tackling cutting-edge engineering challenges to bring revolutionary products to life.
 
 
 
 About The Role
 
 
 
 As a
 
 data scientist intern
 
 , you be joining the ML / research team to develop new tools and techniques for data processing, data analysis, and improving our technology stack. You&rsquo;ll be responsible for designing, running and analyzing experiments using our system, interpreting results to inform future data collection and hardware design, and improving our decoding algorithms. This role will feature hands-on work with our basic signals coming off custom hardware all the way up to studying performance scaling across large numbers of people.
 
 
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Design, implement, and test algorithms for data feature extraction from bio-signals for use in machine learning models.
 </li>
 <li>
 Rapid iteration on experiments for evaluating new hardware prototypes, data collection improvements, and to gain understanding of key aspects of our system.
 </li>
 <li>
 Develop analytical tools for visualization and establish data quality metrics.
 </li>
 <li>
 Work with hardware and electrical engineers to improve the overall sensing stack.
 </li>
 <li>
 Collaborate with ML team on data augmentation, multimodal training, synthetic data experiments for improved generalization
 
 
 </li>
 </ul>
 
 Requirements
 
 
 
 <ul>
 <li>
 Currently enrolled in (or recently graduated from) a PhD program in neuroscience, biomedical engineering, computer science, applied math, or related fields.
 </li>
 <li>
 Effective communication and writing skills.
 </li>
 <li>
 Ability to collaborate effectively across different teams and rapidly adapt to new fields.
 </li>
 <li>
 Fluency in Python (and PyTorch is a plus).
 </li>
 <li>
 Experience with dimensionality reduction techniques and time series data analysis.
 </li>
 <li>
 Independent work ethic, flexibility, and resourcefulness.
 </li>
 <li>
 Enjoy fast moving startup environment, excited to build independently.
 
 
 </li>
 </ul>
 
 Strong candidates may have
 
 
 
 <ul>
 <li>
 Familiarity with real-time human-machine interaction, ranging from automatic speech recognition to closed-loop neural interfaces.
 </li>
 <li>
 Expertise with speech motor control, communication prostheses, and/or speech neuroscience.
 </li>
 <li>
 Prior experience with consumer wearable devices.
 </li>
 <li>
 Basic fundamentals in ML, ML infrastructure: experiment management tracking (e.g. Hydra, WandB) and AWS, Slurm.
 
 
 </li>
 </ul>
 
 Compensation Range
 
 
 
 Hourly determined based on your specific skills and experience
 
 
 
 Details
 
 
 
 <ul>
 <li>
 Company size: 20-30 people
 </li>
 <li>
 Duration: 12 weeks (Start Summer/Fall)
 </li>
 <li>
 This position is full time, on-site in San Francisco
 
 
 </li>
 </ul>
</div>

Data Scientist Intern

Andiamo

<div>
 Data Scientist &ndash; Product &amp; AI
 
 
 
 About The Role
 
 
 
 We are looking for a
 
 Data Scientist
 
 to help solve complex, high-impact problems in product development and AI. You will work with
 
 large-scale, high-dimensional data sets
 
 , applying statistical methods, machine learning, and experimentation to guide product decisions and improve user experiences. Your insights will influence the direction of features, platforms, and strategies used by thousands of organizations.
 
 
 As a mid-level data scientist, you&rsquo;ll own projects end-to-end: defining success metrics, designing experiments, building predictive models, and communicating findings to cross-functional partners. You&rsquo;ll collaborate with product managers, engineers, and designers to turn raw data into actionable insights that drive measurable business and product outcomes.
 
 
 This role is a chance to move beyond dashboards&mdash;you&rsquo;ll uncover patterns, tell compelling stories with data, and contribute to building scalable data science practices that push the boundaries of what&rsquo;s possible.
 
 
 What You&rsquo;ll Do
 
 
 <ul>
 <li>
 Apply Analytical Methods: Use statistical modeling, machine learning, and data visualization to extract insights and guide product strategy.
 </li>
 <li>
 Experiment &amp; Learn: Design, run, and analyze A/B tests and other experiments to evaluate product changes and quantify impact.
 </li>
 <li>
 Build Predictive Models: Develop models that forecast user behavior, product performance, and key metrics.
 </li>
 <li>
 Define Success Metrics: Establish clear goals and KPIs that align product teams around measurable outcomes.
 </li>
 <li>
 Collaborate Across Teams: Partner with engineers, designers, and product leaders to ensure insights are translated into impactful features.
 </li>
 <li>
 Communicate Findings: Present results and recommendations to stakeholders, framing technical insights in clear, actionable terms.
 </li>
 <li>
 Contribute to Data Platforms: Work with engineering partners to improve data pipelines, instrumentation, and experimentation frameworks.
 
 
 </li>
 </ul>
 What We&rsquo;re Looking For
 
 
 <ul>
 <li>
 Professional Experience: Around 5 years of applied data science experience in product analytics, business intelligence, or machine learning.
 </li>
 <li>
 Programming Skills: Proficiency in SQL and Python (or R) for data manipulation, modeling, and analysis.
 </li>
 <li>
 Experimentation: Familiarity with experimental design, causal inference, and A/B testing at scale.
 </li>
 <li>
 Statistical Foundation: Strong grounding in probability, statistics, and data-driven problem solving.
 </li>
 <li>
 Communication: Ability to clearly present technical analyses to non-technical audiences and drive alignment on decisions.
 </li>
 <li>
 Education: Bachelor&rsquo;s degree in Statistics, Mathematics, Computer Science, Engineering, or related field; Master&rsquo;s degree a plus.
 
 
 </li>
 </ul>
 
 Preferred Qualifications
 
 
 
 <ul>
 <li>
 Experience working with product teams or SaaS platforms.
 </li>
 <li>
 Knowledge of ML frameworks (scikit-learn, TensorFlow, or PyTorch) and data visualization tools (Tableau, Looker, or similar).
 </li>
 <li>
 Exposure to cloud data environments (AWS, GCP, or Azure).
 
 
 </li>
 </ul>
 ✨
 
 Why Join
 
 : This is your chance to tackle challenging data problems in AI and product development. You&rsquo;ll apply advanced methods, work with talented colleagues, and contribute to products that affect millions of users and billions of data points&mdash;all while growing your skills and career.
 
 
 
 About Andiamo
 
 
 
 Talent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world&rsquo;s largest and most well-known companies.
 
 
 For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.
 
 
 Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
</div>

Data Scientist - Global Tech Leader

Datavant

<div><div>Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world's health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient's request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health. 
 
By joining Datavant today, you're stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.</div>
What We're Looking For

We are looking for a motivated Data Scientist to help Datavant revolutionize the healthcare industry with AI. This is a critical role where the right candidate will have the ability to work on a wide range of problems in the healthcare industry with an unparalleled amount of data.

You'll join a team focused on deep medical document understanding, extracting meaning, intent, and structure from unstructured medical and administrative records. Our mission is to build intelligent systems that can reliably interpret complex, messy, and high-stakes healthcare documentation at scale.

This role is a unique blend of applied machine learning, NLP, and product thinking. You'll collaborate closely with cross-functional teams to:
<ul>
<li>Design and develop models to extract entities, detect intents, and understand document structure</li>
<li>Tackle challenges like long-context reasoning, layout-aware NLP, and ambiguous inputs</li>
<li>Evaluate model performance where ground truth is partial, uncertain, or evolving</li>
<li>Shape the roadmap and success metrics for replacing legacy document processing systems with smarter, scalable solutions</li>
</ul>
We operate in a high-trust, high-ownership environment where experimentation and shipping value quickly are key. If you're excited by building systems that make healthcare data more usable, accurate, and safe, please reach out.

What You Will Do
<ul>
<li>Play a key role in the success of our products by developing models for document understanding tasks.</li>
<li>Perform error analysis, data cleaning, and other related tasks to improve models.</li>
<li>Collaborate with your team by making recommendations for the development roadmap of a capability.</li>
<li>Work with other data scientists and engineers to optimize machine learning models and insert them into end-to-end pipelines.</li>
<li>Understand product use-cases and define key performance metrics for models according to business requirements.</li>
<li>Set up systems for long-term improvement of models and data quality (e.g. active learning, continuous learning systems, etc.).</li>
</ul>
What You Need to Succeed
<ul>
<li>6+ years of experience with data science and machine learning in an industry setting, particularly in designing and building NLP models.</li>
<li>Expertise with Python</li>
<li>Experience with the latest developments in language models (transformers, LLMs, etc.)</li>
<li>Proficiency with standard data analysis toolkits such as SQL, Numpy, Pandas, etc.</li>
<li>Proficiency with deep learning frameworks like PyTorch (preferred) or TensorFlow</li>
<li>Industry experience shepherding ML/AI projects from ideation to delivery</li>
<li>Demonstrated ability to influence company KPIs with AI</li>
<li>Demonstrated ability to navigate ambiguity</li>
</ul>
What Helps You Stand Out
<ul>
<li>Experience with document layout analysis (using vision or multi-modal approaches).</li>
<li>Experience with Spark/PySpark</li>
<li>Experience with Databricks</li>
<li>Experience in the healthcare industry</li>
</ul>
After 3 Months, You Will&hellip;
<ul>
<li>Have a strong grasp of technologies upon which our platform is built.</li>
<li>Be fully integrated into ongoing model development efforts with your team.</li>
</ul>
After 1 Year, You Will&hellip;
<ul>
<li>Be independent in reading literature and doing research to develop models for new and existing products.</li>
<li>Have ownership over models internally, communicating with product managers, customer success managers, and engineers to make the model and the encompassing product succeed.</li>
<li>Be a subject matter expert on Datavant's models and a source from which other teams can seek information and recommendations.</li>
</ul>
#LI-BC1<div>
To ensure the safety of patients and staff, many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot, Tdap, COVID-19, etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working, exemptions may be available on the basis of disability, medical contraindications to the vaccine or any of its components, pregnancy or pregnancy-related medical conditions, and/or religion.
 
 
This job is not eligible for employment sponsorship. 
 
Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, or other legally protected status. To learn more about our commitment, please review our EEO Commitment Statement here. Know Your Rights, explore the resources available through the EEOC for more information regarding your legal rights and protections. In addition, Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay. 
 
At the end of this application, you will find a set of voluntary demographic questions. If you choose to respond, your answers will be anonymous and will help us identify areas for improvement in our recruitment process. (We can only see aggregate responses, not individual ones. In fact, we aren't even able to see whether you've responded.) Responding is entirely optional and will not affect your application or hiring process in any way. 
 
Datavant is committed to working with and providing reasonable accommodations to individuals with physical and mental disabilities. If you need an accommodation while seeking employment, please request it here, by selecting the 'Interview Accommodation Request' category. You will need your requisition ID when submitting your request, you can find instructions for locating it here. Requests for reasonable accommodations will be reviewed on a case-by-case basis. 
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Senior Data Scientist, NLP

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