Senior Data Scientist, Risk and Fraud

Job Description

About the company

Robinhood is democratizing finance for all! With customers at the heart of our decisions, Robinhood is lowering barriers, removing fees, and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.

Robinhood is a fast-growing company and was recognized as a CNBC Disruptor 50 and a LinkedIn Top Startup in 2019. We’re continuing to grow and are looking for incredible talent that can help us achieve our mission.

Robinhood is headquartered in Menlo Park, California, with offices in Lake Mary, Florida, Denver, Colorado, and London, UK.

About the Role

Insights from data power most decisions at Robinhood and our company trajectory is defined by the systems, tools, and analytics powered by this exceptional team. As a Data Scientist working on Risk you would work with engineers, product managers and operations teams across the company to understand and mitigate the risks to our business.

Robinhood faces unique data challenges with a focus on integrating multifaceted data streams such as rapidly changing market data, user data based on app activity, and brokerage operations data to understand user behavior and the risks to our business.

We are looking for experienced Data Scientists to help detect and reduce risk to Robinhood - a crucial role to our business and customers. The ideal candidate is passionate about understanding the different risk vectors at a fast-growing company and building solutions to mitigate these risks. This team is part of the larger Data Team here at Robinhood.

Your day-to-day will involve:

• Combining knowledge of several research domains to improve our understanding of different risks to Robinhood and help power decisions
• Designing new machine learning systems to power the fraud prevention and risk reduction efforts at Robinhood
• Improving the statistical methodology backing our fraud labeling
• Building statistical models to predict user behavior and risks to the business
• Adapting machine learning algorithms to reduce risk across different areas of the product such as money movements, identity, etc.

Some things we consider critical for this role:

• Graduate degree in a quantitative field such as mathematics, statistics, engineering or natural sciences (or equivalent research experience)
• Solid understanding of statistical analysis and machine learning algorithms
• Excellent programming skills, including expert level familiarity with either Python or R programming languages
• At least 6 years of experience working in a research setting in academic or commercial setting
• At least 2 years of experience working in the Risk and Fraud domain

Bonus points:

• Passion for working and learning in a fast-growing company

Feeling ready to give 100% to democratizing finance for all? We’d love to have you apply, even if you feel unsure about whether you meet every single requirement in this posting. At Robinhood, we’re looking for people invigorated by our mission, not just those who simply check off all the boxes.