Senior Associate, Data Scientist - Beyond AML Modeling & Innovations

Capital One’s Enterprise Risk Organization is building new ways to assess risk, and the Beyond AML Modeling & Innovations (BAMI) team sits at the center of those efforts. In this Senior Associate, Data Scientist role, you will develop and deploy AI and machine learning capabilities that help modernize risk assessment at scale.

This position is based in McLean, VA (onsite) and focuses on turning large volumes of numeric and textual data into practical model-driven insights using a modern technology stack.

What you’ll do

• Work with a cross-functional group of data scientists, software engineers, and product managers to deliver customer-focused solutions
• Use a broad toolkit including Python, Conda, AWS, H2O, Spark, and more to identify insights in large structured and unstructured datasets
• Build machine learning models across the full lifecycle, from design and training through evaluation, validation, and implementation
• Apply strong communication skills to connect complex technical work to measurable business goals

Team context

The Beyond AML Modeling & Innovations (BAMI) team leverages AI to modernize and transform how risk is assessed. The work includes driving 0-to-1 initiatives using approaches such as traditional machine learning, natural language processing, graph-based modeling, and Generative AI to tackle novel and complex problems.

Required qualifications

• Currently has, or is in the process of obtaining one of the following (with the expectation that the required degree will be completed on or before the scheduled start date): a Bachelor’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
• Currently has, or is in the process of obtaining one of the following (with the expectation that the required degree will be completed on or before the scheduled start date): a Master’s Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration

Technologies

• Python, Conda, AWS, H2O, Spark, Scala, R, SQL

Ideal candidate profile

• Innovative: research and evaluate emerging technologies
• Creative: bring structure to large, undefined problems
• Technical: comfortable with open-source languages and focused on continued development
• Statistically-minded: build, validate, and backtest models; interpret a confusion matrix or ROC curve; experience with clustering, classification, sentiment analysis, time series, and deep learning
• Data-focused: retrieve, combine, and analyze data from varied sources and formats

Preferred qualifications

• Master’s degree in a STEM field (Science, Technology, Engineering, Mathematics), or PhD in a STEM field
• Experience working with AWS
• At least 2 years of experience in Python, Scala, or R
• At least 2 years of experience with machine learning
• At least 2 years of experience with SQL

Compensation

• McLean, VA: USD 135,600 - 154,800 per year
• Richmond, VA: USD 123,300 - 140,700 per year

Minimum experience: 2 years