Principal Associate, Data Scientist - SBB Fraud

Capital One • McLean, VA

6d

About The Position

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

The position uses technologies such as Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. It involves the full machine-learning model lifecycle, from design and training through evaluation, validation, and implementation, as well as communicating technical work in terms of tangible business goals. The ideal candidate has strong statistical and data-analysis skills, a customer-first approach, and hands-on experience developing data science solutions with open-source tools and cloud platforms.

Requirements

• Currently has, or is obtaining by the scheduled start date, a bachelor's degree in a quantitative field and at least 5 years of experience performing data analytics; or a master's degree in a quantitative field or an MBA with a quantitative concentration and at least 3 years of data analytics experience; or a PhD in a quantitative field.
• Experience building, validating, and backtesting models and interpreting measures such as confusion matrices and 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.
• Strong interpersonal skills to communicate technical work in business terms.

Nice To Haves

• Master’s degree in a STEM field plus 3 years of data analytics experience, or a PhD in a STEM field.
• At least 3 years of machine-learning experience.
• 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 technologies.
• At least 3 years of experience with SQL.
• At least 1 year of experience working with AWS.

Responsibilities

• Partner with data scientists, software engineers, and product managers to deliver a product customers love.
• Use technologies including Python, Conda, AWS, H2O, and Spark to uncover insights in large volumes of numeric and textual data.
• Build machine-learning models through design, training, evaluation, validation, and implementation.
• Translate complex work into tangible business goals.
• Help develop, deploy, and manage fraud models that make intelligent decisions.

Benefits

• Comprehensive health, financial, and other benefits supporting total well-being.
• Eligibility for performance-based incentive compensation, which may include cash bonuses and/or long-term incentives.

What This Job Offers

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