Pay
$118K–$195K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Menlo Park, CA
Actively hiring, first seen by us 1 day agoEnhance statistical methods behind the experimentation platform, including A/B testing
Partner with engineering to build scalable experimentation tools and infrastructure
Integrate AI-powered capabilities into the experimentation platform to automate workflows
Advise data science and product teams on complex experimental designs and causal inference
Shape the experimentation platform roadmap and drive solutions to adoption
Enhance the statistical methodologies underpinning the experimentation platform, including A/B testing and advanced techniques
Partner with engineering to build scalable tools and infrastructure for experimentation
Identify and drive opportunities to integrate AI-powered capabilities into the experimentation platform, automating workflows
Serve as a statistical expert and trusted partner to data science and product teams, providing guidance on complex experimental designs and causal inference challenges
Shape the experimentation platform roadmap by identifying high-impact opportunities, prioritizing initiatives, and driving solutions from concept through implementation and adoption
Master's or PhD in a quantitative field (e.g., statistics, economics, mathematics, engineering, natural sciences)
3+ years of experience with A/B testing, causal inference, experimental design, and statistical analysis in a tech environment
Deep expertise in statistical methods such as multivariate testing, adaptive experimentation, Bayesian inference, and machine learning techniques
Proficiency in Python or R for data analysis and experimentation workflows
Experience partnering with engineering and product teams to translate statistical methodologies into production-ready tools and platform capabilities
Strong communication skills, with the ability to explain complex statistical concepts and influence technical and non-technical stakeholders
Experience building experimentation platforms or integrating AI-powered capabilities into data science workflows is a plus
WHAT YOU BRING • Master's or PhD in a quantitative field (e.g., statistics, economics, mathematics, engineering, natural sciences) • 3+ years of experience with A/B testing, causal inference, experimental design, and statistical analysis in a tech environment
From the employer’s posting.
Actively hiringFirst seen by us 1 day ago, still listed, and not a repost of an earlier posting.
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
$118K–$195K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 3,828 postings in the last year. Stated ranges, not salaries paid.
Day 1
Early. Similar jobs usually come down between day 8 and day 60.
At Robinhood, jobs usually come down by about day 37.
From 11,873 similar postings that came down, and 11 of Robinhood’s. Coming down is not always a hire.
9 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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• Deep expertise in statistical methods such as multivariate testing, adaptive experimentation, Bayesian inference, and machine learning techniques • Proficiency in Python or R for data analysis and experimentation workflows • Experience partnering with engineering and product teams to translate statistical methodologies into production-ready tools and platform capabilities
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New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Our mission is to democratize finance for all. An estimated $124 trillion of assets will be inherited by younger generations in the next two decades. The largest transfer of wealth in human history. If you’re ready to be at the epicenter of this historic cultural and financial shift, keep reading.
ABOUT THE TEAM + ROLE
We are building an elite team, applying frontier technologies to the world's biggest financial problems. We're looking for bold thinkers. Sharp problem-solvers. Builders who are wired to make an impact. Robinhood isn't a place for complacency, it's where ambitious people do the best work of their careers. We're a high-performing, fast-moving team with ethics at the center of everything we do. Expectations are high, and so are the rewards.
The Experimentation Platform team at Robinhood builds the systems and infrastructure that power our company-wide experimentation efforts. Our mission is to enable rapid, trustworthy, and statistically sound experimentation at scale, so teams can learn quickly and make confident decisions. We partner closely with engineering, product, and data teams across the company. The team's work has a direct impact on product velocity and business outcomes. Together, we're driving a culture of data-informed innovation across Robinhood.
As a Senior Data Scientist on the Experimentation Platform team, you'll play a key role in shaping the statistical foundations of our experimentation systems. You'll collaborate closely with engineering, product, and data partners to advance best practices in A/B testing, improve experiment velocity, and build capabilities that help Robinhood scale experimentation effectively. You'll also explore how AI-powered capabilities can automate workflows and strengthen decision-making, while serving as a trusted statistical partner to data science and product teams. This is a high-impact role with the opportunity to define how we learn and iterate across our products!
This role is based in our Menlo Park, CA office, with in-person attendance expected at least 3 days per week.
At Robinhood, we believe in the power of in-person work to accelerate progress, spark innovation, and strengthen community. Our office experience is intentional, energizing, and designed to fully support high-performing teams.
WHAT YOU'LL DO
• Enhance the statistical methodologies underpinning the experimentation platform, including A/B testing and advanced techniques
• Evaluate current experimentation practices across Robinhood and identify areas for improvement
• Partner with engineering to build scalable tools and infrastructure for experimentation
• Identify and drive opportunities to integrate AI-powered capabilities into the experimentation platform, automating workflows, accelerating experimentation velocity, and improving decision-making
• Develop and champion experimentation best practices, enabling teams to design, analyze, and interpret experiments with statistical rigor
• Serve as a statistical expert and trusted partner to data science and product teams, providing guidance on complex experimental designs and causal inference challenges
• Shape the experimentation platform roadmap by identifying high-impact opportunities, prioritizing initiatives, and driving solutions from concept through implementation and adoption
WHAT YOU BRING
• Master's or PhD in a quantitative field (e.g., statistics, economics, mathematics, engineering, natural sciences)
• 3+ years of experience with A/B testing, causal inference, experimental design, and statistical analysis in a tech environment
• Deep expertise in statistical methods such as multivariate testing, adaptive experimentation, Bayesian inference, and machine learning techniques
• Proficiency in Python or R for data analysis and experimentation workflows
• Experience partnering with engineering and product teams to translate statistical methodologies into production-ready tools and platform capabilities
• Strong communication skills, with the ability to explain complex statistical concepts and influence technical and non-technical stakeholders
• Experience building experimentation platforms or integrating AI-powered capabilities into data science workflows is a plus
WHAT WE OFFER
• Challenging, high-impact work to grow your career
• Performance driven compensation with multipliers for outsized impact, bonus programs, equity ownership, and 401(k) matching
• Top Tier benefits to fuel your work, including 100% paid health insurance for employees with 90% coverage for dependents
• Access to the Robinhood Employee Fund that gives eligible US employees the opportunity to invest in a private employee fund that provides exposure to Robinhood Ventures funds.
• Access to the best AI tools on the market and continuous AI skill-building for every employee, technical or not.
• Lifestyle wallet - a highly flexible benefits spending account for wellness, learning, and more
• Employer-paid life & disability insurance, fertility benefits, and mental health benefits
• Time off to recharge including company holidays, paid time off, sick time, parental leave, and more!
• Exceptional office experience with catered meals, events, and comfortable workspaces.
In addition to the base pay range listed below, this role is also eligible for bonus opportunities + equity + benefits.
Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. The expected base pay range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. For other locations not listed, compensation can be discussed with your recruiter during the interview process.
Base Pay Range:
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If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.
AI Usage Disclosure: Robinhood uses artificial intelligence (AI) tools to support parts of our recruiting process. These tools enhance the efficiency and consistency of our hiring process; however, all hiring decisions are made by our hiring teams.
Robinhood provides equal opportunity for all applicants, offers reasonable accommodations upon request, and complies with applicable equal employment and privacy laws. Inclusion is built into how we hire and work—welcoming different backgrounds, perspectives, and experiences so everyone can do their best. Please review the Privacy Policy for your country of application.
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Menlo Park, CA
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