Principal Associate, Data Science

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VANew York, NYRichmond, VA
Salary: $161,800–$184,600 / yr
Posted: 6 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $180k

This role $173k

$133k most similar roles pay here $229k

This role pays less than 52% of similar roles. Most pay $142,162–$218,750 — the shaded band above. At the midpoint, this role pays about $173k versus about $180k 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 889 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 886 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 (Upmarket Segments), you will join a team focused on leveraging advanced machine learning and computing technologies to uncover insights within massive volumes of numeric and textual data. You will collaborate with cross-functional teams of software engineers and product managers to build machine learning models through every phase of development, including design, training, evaluation, validation, and implementation. The role requires proficiency in a technical stack featuring Python, Conda, AWS, H2O, Spark, SQL, Scala, and R. You will apply expertise in clustering, classification, sentiment analysis, time series, and deep learning to solve complex problems. This position addresses the challenge of processing billions of customer records to provide personalized credit card offers and data-driven decision-making within the financial services sector.

Skills

Python AWS H2O Spark SQL Conda Scala R Machine Learning Deep Learning Sentiment Analysis Time Series Clustering Classification Big Data Cloud Computing

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Use a broad stack of technologies like Python, Spark, and AWS to extract insights from large volumes of numeric and textual data.
Translate complex technical findings into tangible business goals for stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods to improve existing processes.
Solve large, undefined problems by identifying and defining clear paths forward.
Retrieve, combine, and analyze data from a variety of sources and structures to inform decision-making.
Develop data science solutions using open-source tools and cloud computing platforms.

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.
A Master's degree in a STEM field plus 3 years of experience in data analytics (preferred).
A PhD in a STEM field (preferred).
At least 1 year of experience working with AWS (preferred).
At least 3 years of experience with Python, Scala, or R (preferred).
At least 3 years of experience with machine learning and SQL (preferred).

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