Director, Data Science

Capital One Financial

Confirmed live today High trust

Quick summary

Work type: On-site
Location: McLean, VASan Francisco, CACambridge, MARichmond, VANew York, NY
Salary: $269,100–$307,200 / yr
Employment: Full-time
Posted: 2 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 $237k

This role $288k

$172k most similar roles pay here $322k

This role pays more than 84% of similar roles. Most pay $196,962–$278,000 — the shaded band above. At the midpoint, this role pays about $288k versus about $237k 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 1554 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 796 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Director, Data Science

Role Posting Log in to save

Director, Data Science joins a new science team focused on building a portfolio of agentic AI products, including autonomous coding agents and context engineering, to transform internal engineering organizations and business lines. The role involves designing AI/ML models through all phases of development, from training and evaluation to implementation. You will also own the science guiding these products by designing A/B tests, modeling telemetry, and translating complex results into strategic guidance for leadership. To succeed, you will utilize a technical stack including Python, Conda, AWS, H2O, and Spark to analyze large volumes of numeric and textual data. The position requires expertise in clustering, classification, sentiment analysis, time series, and deep learning to solve problems related to automated model development lifecycles and enterprise-scale data utilization within the financial services domain.

Skills

Python AWS Spark H2O Conda Machine Learning Deep Learning Scala R Big Data Sentiment Analysis Time Series Clustering Classification Cloud Computing

What you'll do

Design and build machine learning models through all phases of development including training, evaluation, and validation.
Develop agentic AI products such as autonomous coding agents and context engineering tools for internal organizations.
Design experiments and A/B tests to measure the impact of AI solutions across the enterprise.
Analyze and model telemetry data to provide actionable insights for C-suite leadership.
Use Python, Spark, and AWS to extract insights from large volumes of numeric and textual data.
Translate complex technical findings into tangible business goals and strategic guidance for stakeholders.
Research and evaluate emerging technologies to maintain a state-of-the-art AI/ML roadmap.

What we're looking for

A Bachelor's degree in a quantitative field plus 9 years of experience performing data analytics.
A Master's degree in a quantitative field or an MBA with a quantitative concentration plus 7 years of experience performing data analytics.
A PhD in a quantitative field plus 4 years of experience performing data analytics.
At least 4 years of experience leveraging open source programming languages for large scale data analysis.
At least 4 years of experience building and deploying AI/ML models in production.
At least 4 years of experience designing and analyzing A/B tests.
PhD in a STEM field plus 5 years of experience in data analytics (preferred).
Experience with AWS, Python, Scala, R, or Spark (preferred).

Save