Manager, Data Scientist

Capital One Financial

Confirmed live yesterday Trusted

Quick summary

Work type: On-site
Location: McLean, VANew York, NY
Salary: $197,300–$225,100 / yr
Posted: 17 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 $171k

This role $211k

$121k most similar roles pay here $236k

This role pays more than 76% of similar roles. Most pay $131,737–$211,200 — the shaded band above. At the midpoint, this role pays about $211k versus about $171k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 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 - Card Mainstreet Acquisitions joins the Mainstreet Acquisitions team to serve as a technical and analytical driver for multi-model decisioning pipelines and valuations frameworks. The role involves identifying and mitigating systemic risks within new business decisioning infrastructure through integrated monitoring, utilizing advanced statistical tools to find vulnerabilities, and building solutions centered on Large Language Models and Agentic AI. You will collaborate with cross-functional teams of data scientists, analysts, and engineers to deliver products that improve customer-facing policies. The position requires expertise in machine learning, large-scale data analysis, and relational databases. Key technologies include Python, Scala, R, SQL, and AWS cloud computing platforms. The work focuses on the intersection of model architecture, risk strategy, and emerging AI capabilities to solve complex problems within credit programs and automated decisioning systems.

Skills

Machine Learning LLMs Agentic AI Python SQL Scala R AWS Relational Databases Big Data Deep Learning Time Series Sentiment Analysis Clustering Classification Statistical Modeling Cloud Computing

What you'll do

Identify and mitigate systemic risks within multi-model business decisioning infrastructure through integrated monitoring frameworks.
Use advanced statistical tools to identify gaps and vulnerabilities in existing or new infrastructures.
Build and deploy technical solutions centered on Large Language Models (LLMs) and Agentic AI.
Develop predictive models using machine learning techniques and large-scale cloud-based processing.
Translate complex technical data into tangible business goals for cross-functional stakeholders.
Extract actionable insights from diverse data sources to improve customer-facing credit policies.
Manage the end-to-end lifecycle of model development, including validation and backtesting.

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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