Role overview
- 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
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
- Experience at a fintech company or high-growth startup
- Experience with Looker in a developer capacity (writing LookML, creating views and explores, building dashboards, etc.)
- SIE, Series 7, Series 63, Series 57, Series 24
The expected salary range for this role is based on the location where the work will be performed and is aligned to one of 3 compensation zones. This role is also eligible to participate in a Robinhood bonus plan and Robinhoodâs equity plan.
US Zone 1: $157000 - $185000
US Zone 2: $139000 - $163000
US Zone 3: $122000 - $144000
Base pay for the successful applicant will depend on a variety of job-related factors, which may include education, training, experience, location, business needs, or market demands. You can view comp zones for our US office locations in the table below. For other locations not listed, compensation can be discussed with your recruiter during the interview process.
Office locations (by comp zone)
US Zone 1: Menlo Park, NYC, Seattle, Washington DC
US Zone 2: Denver, Westlake (Dallas), Chicago
US Zone 3: Lake Mary
Weâre looking for more growth-minded and collaborative people to be a part of our journey in democratizing finance for all. If youâre ready to give 100% in helping us achieve our missionâweâd 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 drive to change the world, not just those who simply check off all the boxes.
Robinhood promotes diversity and provides equal opportunity for all applicants and employees. We are dedicated to building a company that represents a variety of backgrounds, perspectives, and skills. We believe that the more inclusive we are, the better our work (and work environment) will be for everyone. Additionally, Robinhood provides reasonable accommodations for candidates on request and respects applicants' privacy rights. To review Robinhood's Privacy Policy please visit Robinhood - US Applicant Privacy Policy. If you are an applicant located in the UK or EEA, please visit the Robinhood UK/EEA Applicant Privacy Policy.
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