- Menlo Park
- Date Posted
- Sep. 8, 2021
- Data Science
Join a leading fintech company that’s democratizing finance for all.
Robinhood was founded on a simple idea: that our financial markets should be accessible to 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.
Just as we focus on our customers, we also strive to create an inclusive environment where our employees can thrive and do impactful work. We are proud of the world class products and company culture we continue to build and have been recognized as:
- A Great Place to Work
- A CNBC Disruptor 50 in 2019 and 2020
- A LinkedIn Top Startup in 2017, 2018, 2019 and 2020
- Robinhood is backed by leading investors that include DST Global, Index Ventures, NEA, Ribbit Capital, Thrive Capital, and Sequoia.
- Check out life at Robinhood on The Muse!
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 Science Analyst in the Risk and Fraud team, you would work with engineers, product managers and operations teams across the company to understand and mitigate monetary risks to our business.
We are looking for experienced analysts to help detect and reduce fraud risk to Robinhood - a crucial role for our ecosystem. The ideal candidate is passionate about understanding the different risk vectors at a fast-growing fintech and building data driven solutions to mitigate these risks. This team is part of the larger Data Team here at Robinhood.
Your day-to-day will involve:
- Working with partners to identify the key metrics their product should track and developing and sharing fraud related analysis, guidance, and dashboards to continuously measure these
- Powering quick decisions by answering business questions by querying our vast datasets
- Actively suggesting policies to mitigate fraud and build a trustworthy Robinhood platform
- Adapting quantitative techniques to solve problems surfaced by multiple perspectives
- Mentoring others as needed to democratize the use of data within the company
- Minimum 5+ years of experience working in product analytics or product data science acting as the analytics voice in consumer product pods
- Graduate degree in a quantitative field such as mathematics, statistics, computer science, engineering or natural sciences (or equivalent research/work experience)
- Solid understanding of unsupervised learning, statistical analysis and models as it relates to fraud detection
- Excellent programming skills, including expert level familiarity with either Python or R programming languages
- At least 6 years of work experience, either in a research/ academic or commercial/ industry setting.
- Experience communicating data driven insights
- The ability to use data to advise, persuade, and lead
- Passion for working and learning in a fast-growing company
- Risk & Fraud experience in fintech is a plus
- Strong customer empathy
- Driven sense of curiosity
We’re looking for more growth-minded and collaborative people to be a part our journey in democratizing finance for all. If you’re ready to give 100% in helping us achieve our mission—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, values, and aim to change the world, not just those who simply check off all the boxes.