Senior Manager, Data Science - US Card (Resiliency Intelligence)

Capital One Financial

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: McLean, VANew York, NYCambridge, MA
Salary: $229,900–$262,400 / yr
Employment: Full-time
Posted: 5 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $188k

This role $246k

$138k most similar roles pay here $276k

This role pays more than 89% of similar roles. Most pay $162,000–$214,900 — the shaded band above. At the midpoint, this role pays about $246k versus about $188k 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 1744 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 948 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Senior Manager, Data Science - US Card (Resiliency Intelligence)

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Senior Manager, Data Science - US Card (Resiliency Intelligence) joins the Mainstreet Growth and Resiliency team to improve financial resiliency through personalized solutions at scale. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to build machine learning models across all development phases, from design and training to evaluation and implementation. You will process large volumes of numeric and textual data to predict customer needs and recommend optimal solutions for those facing financial hardship. The technical stack includes Python, Conda, AWS, H2O, Spark, and open-source libraries like XGBoost and scikit-learn. Your work involves developing custom Python libraries and utilizing statistical models, including clustering, classification, sentiment analysis, time series, and deep learning, to solve complex problems regarding customer treatment and debt resolution in a production environment.

Skills

Python AWS Spark XGBoost scikit-learn H2O Conda Scala R Machine Learning Deep Learning Time Series Sentiment Analysis Clustering Relational Databases Statistical Modeling

What you'll do

Develop machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Use Python, Spark, and AWS to extract insights from large volumes of numeric and textual data.
Build supervised and reinforcement learning models to predict customer needs and recommend optimal solutions.
Write custom Python libraries and utilize open-source ML libraries like XGBoost and scikit-learn.
Translate complex technical findings into tangible business goals for stakeholders.
Manage the end-to-end lifecycle of data science products in both analytical and production environments.
Research and evaluate emerging technologies to improve existing data science methodologies.

What we're looking for

Bachelor's degree in a quantitative field plus 7 years of experience performing data analytics.
Master's degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of experience performing data analytics.
PhD in a quantitative field plus 2 years of experience performing data analytics.
At least 2 years of experience leveraging open source programming languages for large scale data analysis.
At least 2 years of experience working with machine learning.
At least 2 years of experience utilizing relational databases.
PhD in a STEM field plus 4 years of experience in data analytics (preferred).
At least 1 year of experience working with AWS, managing people, or 5 years of experience in Python, Scala, or R for large scale data analysis (preferred).

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