Principal Associate, Data Science

Capital One Financial

Confirmed live 2 days ago Trusted

Quick summary

Work type: On-site
Location: New York, NYMcLean, VA
Salary: $161,800–$184,600 / yr
Posted: 8 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $196k

This role $173k

$146k most similar roles pay here $242k

This role pays less than 60% of similar roles. Most pay $158,450–$232,687 — the shaded band above. At the midpoint, this role pays about $173k versus about $196k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Principal Associate, Data Science

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As a Principal Associate, Data Science - US Card Fraud Authentication Team, you will join a team operating at the critical intersection of fraud defenses and customer experience. You will navigate ambiguous fraud landscapes to identify opportunities where machine learning can drive value while designing technical visions for authentication workflows. Your daily responsibilities include prototyping innovative solutions, analyzing massive datasets to uncover hidden patterns, and building machine learning models through every phase from design to implementation. To succeed, you must utilize a modern tech stack including Python, AWS, Spark, H2O, and SQL. You will also apply statistical expertise in clustering, classification, sentiment analysis, time series, and deep learning. This role focuses on solving the technical challenge of staying ahead of evolving fraud patterns while optimizing authentication decisioning for credit card transactions.

Skills

Python AWS Spark H2O SQL Machine Learning Scala R Deep Learning Time Series Clustering Classification Sentiment Analysis Big Data Statistical Modeling

What you'll do

Identify opportunities within ambiguous fraud landscapes where machine learning can drive business value.
Design technical visions for authentication workflows by evaluating feasibility and prototyping innovative ML solutions.
Analyze massive datasets using Spark, AWS, and SQL to uncover patterns for fraud prevention.
Develop machine learning models through all phases of design, training, evaluation, validation, and implementation.
Translate complex technical findings into actionable business strategies to influence stakeholders and meet goals.
Utilize Python, Scala, or R to build scalable data science solutions in a cloud environment.

What we're looking for

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 experience performing data analytics.
A PhD in a quantitative field.
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.
Experience building and validating models using techniques like clustering, classification, sentiment analysis, time series, and deep learning.

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