Role overview
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 and providing greater access to financial information. Together, we are building products and services that help create a financial system everyone can participate in.
As we continue to build...
Weâre seeking curious thinkers looking to co-author the next chapters of our story. Joining now means helping shape our vision, structures and systems; playing a key-role as we launch into our ambitious future.
What you'll work on
- Utilize advanced statistical and machine learning techniques, including gradient boosted machines, to analyze large datasets and identify patterns and trends related to credit risk in the brokerage lending space. Conduct in-depth data analysis to evaluate credit and market risk factors, including credit history, financial statements, collateral valuation, market risks associated with financial assets and derivatives.
- Build machine learning modeling pipelines to support data science in production, including validation & testing for quality control / quality assurance. Monitor and evaluate the performance of risk models, making necessary adjustments and improvements as needed to enhance the accuracy and effectiveness of risk assessments.
- Collaborate with cross-functional teams, including analysts, engineers, and product managers, to understand business requirements and develop effective risk mitigation strategies for brokerage lending activities. History of efficiently deploying models into production quickly and without defect.
- Leverage knowledge of regulatory requirements and compliance related to credit and market risk management, lending practices, options trading, financial derivatives, model risk governance, and model validation. Ensure compliance with model risk governance policies and procedures, including model validation and ongoing model performance monitoring. Collaborate with model validation teams.
- Communicate complex findings and recommendations to stakeholders, including senior management, in a clear and concise manner, enabling informed decision-making. Produce well-written documentation, including model white papers and analysis reports, to support decision-making.
What we're looking for
- Bachelorâs Degree in a quantitative field such as Economics, Mathematics, Engineering, Finance or related field
- 2-5 years of qualifying experience in a professional data analysis capacity
- Proven knowledge of SQL, Python, or R programming languages to drive data analytics solutions
- Passion for performing data deep dives and using statistical techniques to uncover significant insights
- Passionate about crafting data and metrics documentations to enable self-service reporting, and maintaining the consistency and quality of dashboards
- Ability to learn quickly, work independently and apply problem-solving skills to recommend actions that improve the business
Tags & focus areas
Used for matching and alerts on DevFound Scientist Data Science Python R