Senior Associate, Data Scientist - Operational Risk Management

Experteer Overview In this role you will advance Capital One’s operational risk analytics by building and validating ML models at scale. You will collaborate with engineers, product managers, and data scientists to deliver data-driven insights that inform risk management decisions. You’ll explore large numeric and textual datasets, applying NLP and Generative AI to create next-gen risk features. This is a fast-paced, builder-and-communicator role that shapes how the company manages risk and drives efficiency. Compensation / Benefits * Collaborate with cross-functional teams (data scientists, software engineers, product managers) to deliver impactful risk analytics products * Leverage Python, Conda, AWS, H2O, Spark, and related tools to extract insights from large datasets * Develop machine learning models through the full lifecycle: design, training, evaluation, validation, and implementation * Translate complex technical work into clear business goals and outcomes Tasks * Bachelor in a quantitative field with 2+ years of data analytics experience OR Master in a quantitative field or MBA with quantitative concentration * Experience with AWS * 2+ years with Python, Scala, or R * 2+ years of experience with machine learning * 2+ years of experience with SQL * Knowledge of clustering, classification, sentiment analysis, time series, and deep learning * Familiarity with evaluating models using metrics such as ROC and confusion matrix * Strong data wrangling skills across diverse data sources Key requirements * comprehensive health benefits * competitive compensation * incentives including bonus and long-term incentives * inclusive workplace culture

Experteer Overview In this role you will advance Capital One’s operational risk analytics by building and validating ML models at scale. You will collaborate with engineers, product managers, and data scientists to deliver data-driven insights that inform risk management decisions. You’ll explore large numeric and textual datasets, applying NLP and Generative AI to create next-gen risk features. This is a fast-paced, builder-and-communicator role that shapes how the company manages risk and drives efficiency. Compensation / Benefits * Collaborate with cross-functional teams (data scientists, software engineers, product managers) to deliver impactful risk analytics products * Leverage Python, Conda, AWS, H2O, Spark, and related tools to extract insights from large datasets * Develop machine learning models through the full lifecycle: design, training, evaluation, validation, and implementation * Translate complex technical work into clear business goals and outcomes Tasks * Bachelor in a quantitative field with 2+ years of data analytics experience OR Master in a quantitative field or MBA with quantitative concentration * Experience with AWS * 2+ years with Python, Scala, or R * 2+ years of experience with machine learning * 2+ years of experience with SQL * Knowledge of clustering, classification, sentiment analysis, time series, and deep learning * Familiarity with evaluating models using metrics such as ROC and confusion matrix * Strong data wrangling skills across diverse data sources Key requirements * comprehensive health benefits * competitive compensation * incentives including bonus and long-term incentives * inclusive workplace culture