Director, Data Science

Capital One; McLean (VA); On-site; USD 269,000 - 307,000; Full time

Job summary

Capital One is seeking a Director of Data Science to lead enterprise AI initiatives across engineering and business lines. You will design and guide AI strategies, run experiments, and ensure the translation of data insights into tangible business value across billions of records.

You will partner with cross-functional teams, build scalable ML models, and shape the data strategy at enterprise scale while mentoring a growing team of data scientists and engineers.

Qualifications

• Bachelor's degree in a quantitative field plus 9 years of experience performing data analytics.
• Master's degree in a quantitative field (Statistics, Economics, OR Analytics) or MBA with a quantitative concentration plus 7 years of experience performing data analytics.
• 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/deploying AI/ML models in production.
• At least 4 years of experience designing and analyzing A/B tests.

Responsibilities

• Partner with a cross-functional team of data scientists, AI & ML engineers, and product managers to deliver enterprise products customers love.
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Skills

Open source languages

AI/ML model deployment

A/B testing design

Education

Bachelor's Degree in a quantitative field

Master's Degree in a quantitative field or MBA with a quantitative concentration

PhD in a quantitative field

Tools

Spark

AWS

Python

Job description

Director, Data Science Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision‑making. As a Data Scientist at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in AI and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

About the Team

We're building a portfolio of agentic AI products to transform Capital One's engineering organizations and lines of business – autonomous coding agents, context engineering, and agentic model-development lifecycle to name a few. We're creating a new science team to help define the long-term strategy, analyze & optimize impact throughout the ecosystem, and drive business value at enterprise scale.

As a scientist on the team, you'd design AI/ML models and help build the solutions behind these products. You'd also own the science that guides them: designing experiments (A/B tests), modeling telemetry, and turning the results into AI strategy and guidance for C-suite leadership.

In this role, you will:

• Partner with a cross‑functional team of data scientists, AI & ML engineers, and product managers to deliver enterprise products customers love
• Leverage a broad stack of technologies — Python, Conda, AWS, H2O, Spark, and more — to reveal the insights hidden within huge volumes of numeric and textual data
• Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

• Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers.
• Innovative. You continually research and evaluate emerging technologies. You stay current on published state‑of-the‑art methods, technologies, and applications and seek out opportunities to apply them.
• Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea.
• A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You’re passionate about talent development for your own team and beyond.
• Technical. You’re comfortable with open‑source languages and are passionate about developing further. You have hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms.
• Statistically‑minded. You’ve built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru. “Big data” doesn’t faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

• Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 9 years of experience performing data analytics
• A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 7 years of experience performing data analytics
• A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related 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/deploying AI/ML models in production
• At least 4 years of experience designing and analyzing A/B tests

Preferred Qualifications:

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 5 years of experience in data analytics
• 3+ years of experience working with AWS
• 5+ years of experience with Python, Scala, or R for large scale data analysis
• 5+ years of experience with machine learning
• 5+ years of experience with Spark

Salary (Location-Based)

• Cambridge, MA: $269,100 - $307,200 for Dir, Data Science
• McLean, VA: $269,100 - $307,200 for Dir, Data Science
• New York, NY: $293,600 - $335,100 for Dir, Data Science
• Richmond, VA: $244,700 - $279,200 for Dir, Data Science
• San Francisco, CA: $293,600 - $335,100 for Dir, Data Science

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website.

Eligibility varies based on full or part‑time status, exempt or non‑exempt status, and management level. This role is expected to accept applications for a minimum of 5 business days. No agencies please.

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non‑discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug‑free workplace.

Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

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