Principal Associate, Data Science - US Card Fraud Authentication Team

Capital One Financial

Quick summary

Work type
On-site
Location
New York, NY · McLean, VA
Salary
$161,800–$184,600 / yr
Posted
44 days ago

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $173k
This role $173k
$122k most similar roles pay here $226k

This role pays more than 59% of similar roles. Most pay $132,000–$213,532 — the shaded band above. At the midpoint, this role pays about $173k versus about $173k for comparable roles.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 498 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 495 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Principal Associate, Data Science - US Card Fraud Authentication Team

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As a Principal Associate on the US Card Fraud Authentication Data Science team at Capital One, you will lead efforts to identify and mitigate fraud risks while enhancing customer experiences. You will work within a sophisticated tech stack that includes Python, AWS, Spark, H2O, and SQL to analyze large datasets and develop machine learning models for optimizing authentication processes. Your role involves collaborating with cross-functional teams to design innovative solutions, translating complex technical insights into actionable strategies that address evolving fraud patterns. This position requires a deep understanding of statistical methods and the ability to articulate technical concepts to non-technical stakeholders, ensuring alignment between business goals and technological advancements in fraud prevention.

Skills

Python AWS Spark H2O SQL CI/CD

What you'll do

  • Identify fraud patterns and opportunities for ML solutions in ambiguous landscapes.
  • Design technical vision for authentication workflows using modern tech stacks.
  • Uncover hidden patterns in big data to develop actionable fraud-prevention strategies.
  • Prototype innovative machine learning models to enhance fraud detection systems.
  • Communicate complex technical concepts to influence stakeholders and achieve business goals.

What we're looking for

  • At least 3 years of experience in Python and/or Scala/R.
  • Strong background in SQL for data manipulation and analysis.
  • Experience with big data technologies like Spark and AWS.
  • Ability to design and prototype machine learning solutions.
  • Statistically-minded with a focus on fraud pattern recognition.

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