Principal Associate, Data Scientist - SBB Fraud

Capital One • McLean, VA

8d • $161,800 - $184,600

About The Position

Capital One’s Small Business Bank (SBB) Fraud Data Science team develops machine learning models to help protect customers and Capital One from fraud, including transaction fraud, account-opening fraud, and account-takeover fraud. The Principal Associate, Data Scientist partners with data scientists, software engineers, product managers, and other cross-functional colleagues to build, deploy, and manage fraud models that make intelligent decisions.

The role uses technologies such as Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. The data scientist builds machine learning models throughout the development lifecycle, from design and training through evaluation, validation, and implementation, and translates technical findings into tangible business goals. The work emphasizes statistical modeling, data analysis, customer-focused decision-making, open-source tools, and cloud computing.

Requirements

• Currently hold, or be in the process of obtaining by the scheduled start date, a bachelor's degree in a quantitative field plus 5 years of experience performing data analytics; a master's degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of data analytics experience; or a PhD in a quantitative field.
• Quantitative fields include Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field.

Nice To Haves

• A master's degree in a STEM field plus 3 years of experience in data analytics, or a PhD in a STEM field.
• At least 3 years of experience with machine learning.
• At least 1 year of experience with deep learning or emerging AI, such as graphs, embeddings, sequence models, or transformer models.
• At least 3 years of experience with Python, Dask, Spark, or similar tools.
• At least 3 years of experience with SQL.
• At least 1 year of experience working with AWS.
• Experience building, validating, and backtesting statistical models and interpreting confusion matrices or ROC curves.
• Experience with clustering, classification, sentiment analysis, time series, and deep learning.
• Ability to retrieve, combine, and analyze data from varied sources and structures.
• Hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

Responsibilities

• Partner with data scientists, software engineers, product managers, and other cross-functional colleagues to deliver products for customers.
• Use technologies such as Python, Conda, AWS, H2O, and Spark to identify insights in large volumes of numeric and textual data.
• Build machine learning models through design, training, evaluation, validation, and implementation.
• Translate technical work and its complexity into tangible business goals.
• Build, deploy, and manage fraud models that help detect transaction, account-opening, and account-takeover fraud.

Benefits

• Performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.
• Comprehensive health, financial, and other benefits supporting total well-being; eligibility varies by employment status and management level.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior