Manager, Data Science - US Card Customer Management

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: New York, NYMcLean, VACambridge, MARichmond, VA
Salary: $197,300–$225,100 / yr
Employment: Full-time
Posted: 9 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 $202k

This role $211k

$157k most similar roles pay here $239k

This role pays more than 61% of similar roles. Most pay $171,825–$231,187 — the shaded band above. At the midpoint, this role pays about $211k versus about $202k 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 1435 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 702 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Science - US Card Customer Management

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Manager, Data Science - US Card Customer Management joins the US Card data science organization to develop top-tier machine learning solutions for customer management. This role involves collaborating with cross-functional teams of engineers, analysts, and product managers to deliver products that address real-time customer behavioral prediction and valuation forecasts. The successful candidate will build machine learning models through all phases of development, including design, training, evaluation, validation, and implementation. To uncover insights within large volumes of numeric and textual data, the role utilizes a technology stack featuring Python, Conda, AWS, H2O, Spark, and relational databases. Key technical competencies include experience with clustering, classification, sentiment analysis, time series, and deep learning. The position focuses on solving complex problems in the credit card industry by leveraging advanced modeling to improve customer outcomes.

Skills

Python AWS H2O Spark SQL Conda Machine Learning Deep Learning Relational Databases Scala R Sentiment Analysis Time Series Clustering Classification Big Data Data Analytics

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Use Python, Spark, H2O, and AWS to extract insights from large volumes of numeric and textual data.
Develop real-time customer behavioral predictions and valuation forecasts for the card management business.
Translate complex technical findings into tangible business goals for non-technical stakeholders.
Manage and analyze big data from diverse sources and structures to inform decision-making.
Research and evaluate emerging technologies and state-of-the-art methods to improve existing systems.
Solve large, undefined problems by identifying and improving the status quo through innovative analysis.

What we're looking for

Bachelor's degree in a quantitative field plus 6 years of experience performing data analytics.
Master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of experience performing data analytics.
PhD in a quantitative field plus 1 year of experience performing data analytics.
At least 1 year of experience leveraging open source programming languages for large scale data analysis.
At least 1 year of experience working with machine learning.
At least 1 year of experience utilizing relational databases.
PhD in a STEM field plus 3 years of experience in data analytics (preferred).
Experience with AWS, Python, Scala, R, or SQL (preferred).

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