• Principal Associate, Data Scientist
• US Card (Applied GenAI)

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 computing 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.

Team Description:

The Servicing Intelligence team delivers data science solutions to capture value from unstructured, multi-modal data sources — text, image, and audio data. We operate as an applied data science team, building with open source generative AI models and tooling, but prioritizing application over research to scale the adoption of AI with in-market solutions.

You will sit on a team of data scientists that collaborates daily with product, tech, and business teams to embed AI in varied domains, including frontline agent servicing, back office document processing, AI for regulatory compliance, and overall customer experience. Your work will apply generative AI on millions of inputs, spanning from extracting key information from unstructured documents to analyzing call transcripts to resolve the root cause of customer friction.

As a core member of the team, you will be the driving force to create best-in-class products and experiences powered by the latest emerging generative AI technologies.

Role Description:

In this role, you will:

• Apply expertise in unstructured data (text, image) to harness the power of open source large language models (LLMs) and visual language models (VLMs)

• Leverage a broad stack of technologies — Lang Graph, Llama Index, Weights and Biases Weave, Hugging Face, Py Torch, AWS, and more — to automate workflows using huge volumes of text and vision data

• Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.

• Assessing GenAI or LLM-Powered application architectures in production, including best practices for Generative AI development and deployments.

• Define requirements for AI observability, focusing on the traceability of autonomous decisions and comprehensive system audit trails.

• Evaluate the dynamic behavior of AI systems and oversee the development of key continuous monitoring controls and testing, ensuring that non-deterministic outputs and autonomous actions remain within risk appetite.

• Get into the weeds of internal business processes and data operations by guiding annotators to curate high quality, consistent datasets for model training, evaluation, and ongoing AI monitoring.

• Collaborate on a team of data scientists through all phases of project development, from design through training, evaluation, validation, implementation, and maintenance.

• Interact with a variety of internal stakeholders to ensure the alignment of data science solutions with business outcomes.

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 5 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 3 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)

Preferred Qualifications:

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)

• At least 1 year of experience working with AWS

• At least 3 years’ experience in Python, Scala, or R

• At least 3 years’ experience with machine learning

• At least 3 years’ experience with SQL

• At least 2 years’ experience with relational databases

• At least 2 years’ experience AI/ML tools and ecosystems, such as Lang Graph, Llama Index, Weights and Biases Weave, Pytorch, or Hugging Face

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

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Mc Lean, VA: $161,800 - $184,600 for Princ Associate, Data Science

New York, NY: $176,500 - $201,400 for Princ Associate, Data Science

Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.

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.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at Recruiting Accommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

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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).