• Location
    • Menlo Park
  • Date Posted
  • May. 18, 2021
  • Function
  • Data Science
  • Sector
  • Fintech

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. Data Scientists at Robinhood work on statistics, machine learning and experimentation with stakeholders such as product, marketing, engineering, finance, customer support, and compliance to understand and analyze data from all parts of our business to power these decisions. Our company trajectory is defined by the systems, tools, and analytics powered by our exceptional team.

Rapid experimentation allows us to easily incorporate our successful experiments into the frontend product features and backend systems, while simply discarding our failed experiments. The tighter and faster this feedback loop, the more rapidly we will improve our service and grow our business.

Your day-to-day will involve:

  • Delivering features to enhance the Experimentation Platform
  • Designing new measurement systems to power experimentation and decision making at Robinhood
  • Tech Lead for Experiment Analysis: Understand the capabilities of our platform and communicate with other Data Scientists how to best utilize our platform
  • Focusing on experimental design, power analysis / hypothesis testing, confounding, variance estimation, bias-variance tradeoff, correlated data, heterogeneous treatment effects, propensity score methods
  • Supporting Product Engineering teams with experimentation best practices and experiment analyses
  • Developing and sharing insights around the key metrics that drive the company
  • Working with stakeholders to identify the key metrics different departments should track for their experiments
  • Mentoring others as needed to democratize the use of experiments within the company

About you:

  • Masters or PhD in a quantitative field such as mathematics, statistics, econometrics, biostatistics (or equivalent experience)
  • 3+ years of experience (for masters, 5+ years of experience) as a data scientist focusing on building data solutions and/or machine learning products
  • Experience working on Experimentation (A/B testing)
  • Experience with causal inference tools and practices (e.g. regression discontinuity, synthetic controls, difference-in-differences, doubly robust treatment effect estimation, interrupted time-series, local average treatment effect estimation, etc.)
  • Expert level SQL skills
  • Proficiency in Python or R
  • Experience with communicating data driven insights

Bonus points:

  • Passion for working and learning in a fast-growing company
  • Familiarity with heterogeneous treatment effect estimation, causal/double machine learning methods/frameworks
  • Familiarity with experimentation under interference/with network effects
  • Familiarity with best practices from “Online Trustworthy Controlled Experiments”

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.