Principal Associate, Data Science, US Card (Upmarket Segments)

Capital One Financial

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Quick summary

Work type: On-site
Location: McLean, VANew York, NYRichmond, VA
Salary: $161,800–$184,600 / yr
Employment: Full-time
Posted: 4 days ago
Freshness: Confirmed live today
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 $229k

below market most similar roles pay here above market

This role pays less than 52% of similar roles. Most pay $145,200–$214,500 — the blue 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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 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 (Upmarket Segments)

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The Principal Associate, Data Science - US Card (Upmarket Segments) joins a team focused on delivering data-driven solutions for the credit card industry. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to build machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. You will leverage a broad technology stack including Python, Conda, AWS, H2O, Spark, Scala, and R to reveal insights within huge volumes of numeric and textual data. Key responsibilities involve translating complex technical work into tangible business goals while applying expertise in clustering, classification, sentiment analysis, time series, and deep learning. This position addresses the technical challenge of analyzing billions of customer records to unlock financial opportunities.

Skills

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

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, and implementation.
Leverage a broad technology stack including Python, AWS, H2O, and Spark to extract insights from large datasets.
Analyze and combine data from a variety of sources and structures to identify hidden patterns.
Translate complex technical work into tangible business goals for non-technical stakeholders.
Research and evaluate emerging technologies and state-of-the-art methods for application in data science.
Develop data science solutions using open-source tools and cloud computing platforms.
Interpret statistical metrics such as confusion matrices and ROC curves to validate model performance.

What we're looking for

Must have a Bachelor's degree in a quantitative field plus 5 years of data analytics experience.
Must have a Master's degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of data analytics experience.
Must have a PhD in a quantitative field.
Must have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Must have experience with clustering, classification, sentiment analysis, time series, and deep learning.
Must have experience building, validating, and backtesting models while interpreting confusion matrices or ROC curves.
Must have experience retrieving, combining, and analyzing data from a variety of sources and structures.
Preferred: Master’s or PhD in a STEM field plus 3 years of data analytics experience.
Preferred: At least 1 year of experience working with AWS.
Preferred: At least 3 years of experience in Python, Scala, or R.
Preferred: At least 3 years of experience with machine learning.
Preferred: At least 3 years of experience with SQL.

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