Principal Associate, Data Scientist - Anti-Money Laundering

About the role

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, business analysts, risk managers, and product owners to deliver industry-leading risk management products
• Leverage a broad stack of tools and technologies — Python, Conda, AWS, Spark, dbt, and more — to build production-ready pipelines for data sourcing, model development, and model scoring
• Build machine learning models and AI tools through all phases of development, from design through training, evaluation, validation, and implementation
• Fine tune, evaluate, customize, and productionize Large Language Models (LLMs)
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

Requirements

• Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• Technical. You’re comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
• Statistically-minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

Qualifications

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained 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 5 years of experience performing data analytics
• 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 plus 3 years of experience performing data analytics
• A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 3 years of experience performing data analytics

Preferred Qualifications

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics
• At least 2 years’ experience in AML modeling or related domain (e.g. Fraud, Credit Risk, etc.)
• At least 1 year of experience developing and evaluating production-grade GenAI, Agentic AI, and/or LLMs based systems, including experience with vector databases, LLM fine tuning, RAG, and use of LangGraph or LlamaIndex
• At least 1 year of experience working with AWS
• At least 3 years’ experience in Python and SQL
• At least 3 years’ experience with machine learning

Benefits

The role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Pay

Chicago, IL: $147,100 - $167,900 for Princ Associate, Data Science
McLean, VA: $161,800 - $184,600 for Princ Associate, Data Science
Plano, TX: $147,100 - $167,900 for Princ Associate, Data Science
Richmond, VA: $147,100 - $167,900 for Princ Associate, Data Science

Schedule

This role is full-time.