Phd Science Jobs in Virginia (NOW HIRING)

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by personally customizing each credit card offer using statistical modeling and relational databases, leveraging cutting‑edge technology in 1988. Fast‑forward a few years: our passion for data has driven us to become a Fortune 200 company and a leader in 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 computing and machine learning technologies across billions of customer records so everyday people can save money, time, and reduce financial complexity.

The Entity Resolution Systems team builds and ships state‑of‑the‑art machine learning solutions to support entity resolution within the enterprise. The system powers marketing, customer service, and other business units. We partner with product, technology, and design teams to deliver personalized experiences for data and platform users, driving productivity and innovation. You will be the driving force to experiment, innovate, and create next‑generation experiences powered by the latest emerging ML technologies and agentic software development practices. We are building a modern, extensible entity resolution stack that leverages deep learning, transformer architectures, and graph approaches. The team applies research and methodologies to real‑world problems and delivers scalable solutions for our 100 million+ customers.

• Partner with a cross‑functional team of data scientists, software engineers, and product managers to build a next‑generation entity resolution solution that uses cutting‑edge machine learning to solve real‑world business problems.
• Leverage a broad stack of technologies – Python, AWS, Spark, modern state‑of‑the‑art models such as transformers and graph ML – to uncover insights from large volumes of numeric and textual data.
• Build machine learning models through all phases of development: design, training, evaluation, validation, and implementation.
• Leverage agentic AI tools and workflows to build and test models.
• Translate the complexity of your work into tangible business goals and communicate across teams.

• Innovative – regularly researching and evaluating emerging technologies, staying current with state‑of‑the‑art methods and applying them where appropriate.
• Creative – thrives on defining and tackling large, undefined problems, asking questions, and pushing hard for answers; willing to share new ideas.
• Technical – comfortable with open‑source languages, passionate about development, with hands‑on experience building data science solutions on open‑source tools and cloud platforms.
• Statistically‑minded – has built, validated, and back‑tested models; interprets confusion matrices, ROC curves; experienced with clustering, classification, sentiment analysis, time series, and deep learning.
• A data guru – unafraid of “big data”; skilled at retrieving, combining, and analyzing data from varied sources and structures; understands that data mastery is key to great data science.

• Currently has, or is in the process of obtaining one of the following with the 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 7 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 5 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 2 years of experience performing data analytics.
• At least 2 years of experience leveraging open‑source programming languages for large‑scale data analysis.
• At least 2 years of experience working with machine learning.
• At least 2 years of experience utilizing relational databases.

• PhD in a STEM field (Science, Technology, Engineering, or Mathematics).
• Experience working with AWS.
• At least 5 years of experience in Python, Scala, or R.
• At least 5 years of experience with machine learning.
• At least 5 years of experience with SQL.

McLean, VA: $229,900 – $262,400 for Senior Manager, Data Science

New York, NY: $250 800 – $286 200 for Senior Manager, Data Science

San Jose, CA: $250 800 – $286 200 for Senior Manager, Data Science

This role is also eligible to earn performance‑based incentive compensation, which may include cash bonuses and/or long‑term incentives (LTI). Incentives may 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.

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 applicable laws.

Capital One will consider sponsoring a qualified applicant for employment authorization for this position.

This role is expected to accept applications for a minimum of 5 business days. No agencies please.

Capital One does not provide, endorse, or guarantee and is not liable for third‑party products, services, educational tools, or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe, and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).