Senior Associate, Data Science

Experteer Overview As a Data Scientist on Capital One’s Credit Risk team, you apply statistical and machine learning methods to forecast losses and optimize allowances across the card portfolio. You will collaborate with data scientists, engineers, and product managers to quantify model risk and drive governance for production-ready solutions. You’ll work with a broad tech stack to extract actionable insights from billions of records and present impact to executives. This role offers the chance to modernize loss forecasting and contribute to data transformation at scale. You will help shape the next generation of risk models in a fast-moving, data-centric environment. Compensation / Benefits * Partner with cross-functional teams to identify and quantify model risks * Leverage Python, Conda, AWS, Spark to extract insights from data * Build statistical and ML models to challenge existing production models * Contribute to model governance for future ML models * Present model risk impacts to executives * Support loss forecasting, resilience, outlook, and CCAR initiatives Tasks * Bachelor or Master in a quantitative field (or MBA with quantitative concentration) * 2+ years of data analytics experience (for Bachelor’s path) * Experience with open-source tools and cloud computing * Hands-on model development, validation, and backtesting * Ability to retrieve, combine, and analyze diverse data sources * Strong communication to convey risk implications to leadership Key requirements * salary range by location * performance-based incentive compensation * health benefits * inclusive benefits * career development * flexible work options

a to executives * Support loss forecasting, resilience, outlook, and CCAR initiatives Tasks * Bachelor or Master in a quantitative field (or MBA with quantitative concentration) * 2+ years of data analytics experience (for Bachelor’s path) * Experience with open-source tools and cloud computing * Hands-on model development, validation, and backtesting * Ability to retrieve, combine, and analyze diverse data sources * Strong communication to convey risk implications to leadership Key requirements * salary range by location * performance-based incentive compensation * health benefits * inclusive benefits * career development * flexible work options