Staff Data Scientist (Quantitative Researcher)

Join us in building the future of finance.

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 Investment Strategy team is expanding access to sophisticated investment advice by turning high-quality portfolio management into a scalable, intuitive experience for everyday customers. Sitting at the intersection of markets, product, and customer experience, our team combines rigorous investment thinking with a mobile-first product design. We are dedicated to building accessible investing tools that reach and support millions of people! 

As a Staff Data Scientist (Quantitative Researcher), you will report to the Chief Investment Officer and play a key role in shaping our investment product offerings. In this role, you will build complex portfolio construction factor models, identify critical areas for methodology improvement, and design high-performing investment solutions. You will also collaborate closely with Product, Engineering, Compliance, and Legal to launch these products and bring them directly to our customers.

This role is based in our New York, NY 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

• Partner with the Chief Investment Officer and investment leadership to develop, refine, and maintain complex portfolio construction models.
• Work with large datasets, including unconventional data sources, to predict and test statistical market patterns, conceptualize valuation strategies, and improve mathematical models.
• Backtest and implement financial models and signals in a live trading environment.
• Continuously research and analyze new approaches to building portfolio models, applying knowledge of existing and emerging quantitative finance principles, theories, and techniques to inform investment decisions.
• Partner with product and engineering teams to help design and execute on complex projects and product launches.
• Assist with reviews by Legal & Compliance to develop written policies and procedures when new features are introduced or methodology changes are developed.

What you bring

• 5+ years of quantitative research, quantitative portfolio construction, or machine learning experience, ideally within asset management, a broker-dealer, an RIA, or broader financial services.
• Experience taking machine learning models, research, or quantitative signals into a live investing or production environment.
• Strong proficiency in Python and SQL for quantitative modeling, statistical analysis, and working with large-scale datasets.
• Strong grounding in statistics, machine learning algorithms, and pattern recognition.
• Outstanding communication skills, with a proven ability to translate complex modeling, statistical, or investment concepts for software engineering, product, and compliance partners.
• Comfort with ambiguity, high personal ownership, and the ability to work independently to deliver on critical business milestones.

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 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:

Zone 1 (Menlo Park, CA; New York, NY; Bellevue, WA; Washington, DC)

$217,000—$255,000 USD

Zone 2 (Denver, CO; Westlake, TX; Chicago, IL)

$191,000—$224,000 USD

Zone 3 (Lake Mary, FL; Clearwater, FL; Gainesville, FL)

$170,000—$199,000 USD

Click here to learn more about our Total Rewards, which vary by region and entity.

If our mission energizes you and you’re ready to build the future of finance, we look forward to seeing your application.

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.