Principal Data Scientist

Overview

Principal Associate, Data Scientist - Bank Operations Data Science - Payments Organization

Data is at the center of everything we do. As a startup, Capital One disrupted the credit card industry by personalizing offers using statistical modeling. This role is part of a team that uses data and machine learning technologies to unlock opportunities for customers and the business at a large scale.

As a Data Scientist at Capital One, you’ll be part of a team that’s leading disruption at a whole new scale, working with billions of customer records to deliver insights and capabilities across payment channels.

• Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver a product customers love
• Leverage a broad stack of technologies — Python, Snowflake, and more — to reveal insights from large volumes of numeric and textual data
• Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation
• Translate complex work into tangible business goals
• Collaborate with the Enterprise Payments team to streamline payment/monetary transfer channels, including data ingestion, anomaly detection, and operational efficiencies with agentic processes

• Innovative: researches and applies emerging technologies; stays current on state-of-the-art methods and opportunities to apply them
• Creative: defines big problems, asks questions, and shares new ideas
• Technical: comfortable with open-source tools and cloud computing; hands-on experience developing data science solutions
• Statistically-minded: experience with model development, validation, interpretation of metrics (e.g., ROC, confusion matrices), and methods across clustering, classification, sentiment analysis, time series, and deep learning

• Currently has, or is in the process of obtaining one of the following with expected completion by start date:
  • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or related) plus 5 years of data analytics experience
  • A Master's Degree in a quantitative field or MBA with quantitative concentration plus 3 years of data analytics experience
  • A PhD in a quantitative field

• Master’s Degree in STEM plus 3 years of data analytics experience, or PhD in STEM
• At least 1 year of experience with AWS
• At least 3 years’ experience in Python
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with SQL
• Experience building at least one agentic system
• Experience building at least one machine vision model

The minimum and maximum full-time annual salaries are location-based. Salaries for part-time roles are prorated. This role is eligible for incentive compensation where applicable. Capital One offers a comprehensive benefits package, including health and other well-being programs. Eligibility varies by status and location.

Capital One will sponsor qualified applicants for employment authorization where permissible. Details by location are provided in the job posting. This role is expected to accept applications for a minimum of 5 business days.

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with criminal histories in a manner consistent with applicable laws.

If you require an accommodation during the application process, please contact Capital One Recruiting at or Recruitin All information will be kept confidential and used only to provide needed accommodations.

For technical support or questions about Capital One's recruiting process, please email  Capital One does not provide, endorse, or guarantee third-party products or services advertised on this site. Capital One Financial is composed of multiple entities; postings in Canada, the UK, or the Philippines refer to local Capital One entities.

• Mid-Senior level

• Full-time

• Engineering and Information Technology