Principal Associate, Data Science - US Card Fraud Authentication Team

Capital One•McLean, VA

21h

About The Position

Capital One, a Fortune 200 company and a leader in data-driven decision-making, is seeking a Principal Associate, Data Science for its US Card Fraud Authentication Team. The company has a history of disrupting the credit card industry through personalized offers using statistical modeling and relational databases. As a Data Scientist, you will contribute to the next wave of disruption by leveraging computing and machine learning technologies across billions of customer records to improve financial lives. The US Card Fraud Authentication Data Science team operates at the critical intersection of fraud defenses and customer experience. This team utilizes a modern tech stack including Python, AWS, Spark, H2O, and SQL to analyze complex datasets and optimize authentication decisioning. The mission is to proactively address evolving fraud patterns through rigorous quantitative analysis and the development of scalable machine learning solutions.

Requirements

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.
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 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.
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 PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field).

Nice To Haves

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).
At least 1 year of experience working with AWS.
At least 3 years of experience in Python, Scala, or R.
At least 3 years of experience with machine learning.
At least 3 years of experience with SQL.

Responsibilities

Dive into ambiguous fraud landscapes to identify opportunities where machine learning can drive value.
Help design the technical vision for our authentication workflows, evaluating feasibility and prototyping innovative ML solutions.
Harness our big data ecosystem (Spark, AWS, and more) to uncover hidden patterns in massive datasets, turning raw information into actionable fraud-prevention strategies.
Partner with a cross-functional team of business stakeholders, data scientists, software engineers, and product managers to deliver a product customers love.
Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
Bridge the gap between technical complexity and business strategy, articulating the "why" behind your solutions to influence stakeholders and achieve tangible business goals.