Manager, Data Scientist

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: McLean, VANew York, NYCambridge, MA
Salary: $197,300–$225,100 / yr
Posted: 3 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $185k

This role $211k

$140k most similar roles pay here $234k

This role pays more than 73% of similar roles. Most pay $154,950–$214,500 — the shaded band above. At the midpoint, this role pays about $211k versus about $185k 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 1042 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1036 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Manager, Data Scientist

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Manager, Data Scientist - US Card (Upmarket Acquisitions) joins the US Card Data Science team to build industry-leading machine learning models that power core underwriting decisions for the acquisition and management of credit card customers. Working within a cross-functional environment alongside data engineers, software engineers, and product managers, you will manage the full model lifecycle including design, training, evaluation, validation, and deployment. You will analyze massive volumes of numeric and textual data to uncover insights and translate complex technical work into tangible business goals. The role requires proficiency in Python, Conda, AWS, H2O, Spark, and SQL. Candidates must possess expertise in clustering, classification, sentiment analysis, time series, and deep learning while utilizing open-source tools and cloud computing platforms to solve complex problems regarding credit card offer personalization and risk management.

Skills

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

What you'll do

Build machine learning models through all phases of development including design, training, evaluation, validation, and implementation.
Manage the full lifecycle of models including deployment, monitoring, governance, and ongoing usage expansion.
Analyze large volumes of numeric and textual data using Python, Spark, H2O, and other technologies.
Retrieve and combine data from various sources and structures to identify hidden insights.
Translate complex technical findings into tangible business goals for non-technical stakeholders.
Solve complex problems by identifying and improving the status quo through innovative modeling techniques.
Develop machine learning solutions that power core underwriting decisions for credit card acquisitions and management.

What we're looking for

A Bachelor's degree in a quantitative field plus 6 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 4 years of experience performing data analytics.
A 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.
A 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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