Capital One

Financial Services

PrincipalAssociate,DataScienceUSCardFraudAuthenticationTeam

$162–185k New York, New York, United States FULL TIME Remote Friendly
The Brief

“Principal Associate, Data Science - US Card Fraud Authentication Team at Capital One. Skills: Data Science, machine learning, statistical modeling, quantitative analysis, big data. Dive into ambiguous fraud landscapes to identify opportunities where machine learning can drive value. Design the technical vision for our authentication workflows”

What You'll Achieve.

Optimize authentication decisioning; Stay ahead of evolving fraud patterns; Achieve tangible business goals

Industry & Context.

Financial Services
Problems you'll solve

Dive into ambiguous fraud landscapes to identify opportunities where machine learning can drive value; Harness our big data ecosystem to uncover hidden patterns in massive datasets; Statistically-minded. You’ve built models, validated them, and backtested them.

What They're Looking For.

Must Have

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

Nice to Have

Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, 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

What You'll Do.

Dive into ambiguous fraud landscapes to identify opportunities where machine learning can drive value

Design the technical vision for our authentication workflows

Evaluate feasibility and prototype innovative ML solutions

Harness our big data ecosystem to uncover hidden patterns in massive datasets

Turn raw information into actionable fraud-prevention strategies

Build machine learning models through all phases of development

from design through training

How You'll Work.

Team & Collaboration

Partner with a cross-functional team of business stakeholders, data scientists, software engineers, and product managers to deliver a product customers love

Communication Scope

Articulating the 'why' behind your solutions to influence stakeholders and achieve tangible business goals

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