As a Staff Data Scientist (Quantitative Researcher) at Robinhood, you will play a pivotal role in shaping investment product offerings by building complex portfolio construction models and collaborating with various teams. The Investment Strategy team focuses on expanding access to sophisticated investment advice through innovative tools. This position requires a blend of quantitative research and collaboration with product, engineering, compliance, and legal teams. The role is based in New York, NY, with an expectation of in-person attendance at least three days a week.

• 5+ years of quantitative research, quantitative portfolio construction, or machine learning experience in financial services.
• Experience implementing machine learning models in a live investing environment.
• Strong proficiency in Python and SQL for quantitative modeling and statistical analysis.
• Solid grounding in statistics, machine learning algorithms, and pattern recognition.
• Outstanding communication skills to translate complex concepts for various stakeholders.
• Ability to work independently and manage ambiguity while delivering on critical business milestones.

• Partner with the Chief Investment Officer to develop and maintain complex portfolio construction models.
• Work with large datasets to predict and test statistical market patterns and improve mathematical models.
• Backtest and implement financial models and signals in a live trading environment.
• Research and analyze new approaches to building portfolio models using quantitative finance principles.
• Collaborate with product and engineering teams on complex projects and product launches.
• Assist with Legal & Compliance reviews to develop policies and procedures for new features.