Join Robinhood as a Staff Data Scientist to shape investment product offerings and build complex portfolio models.
Posted by employer 2 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 1 day ago
What you'll build
Must have
Nice to have
Practical constraints
AI in the day-to-day
Access to the best AI tools on the market and continuous AI skill-building for every employee.
Requirements
Not disclosed in this posting: visa sponsorship.
Benefits
Joblaze summary
In the role of Staff Data Scientist (Quantitative Researcher) at Robinhood, the individual will focus on developing and refining complex portfolio construction models while collaborating with various teams to launch investment products. Proficiency in Python and SQL, along with a strong foundation in statistics and machine learning, is essential for success in this position. This role is suited for experienced professionals with a background in quantitative research or financial services, who are comfortable navigating ambiguity and working independently. The team emphasizes high performance and ethical practices in a fast-paced environment.
Joblaze insights
Quick facts
From the original posting
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.
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.
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.
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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