Senior Manager, Data Scientist - Bank Customer Protection Agentic Claims

Capital One • McLean, VA

6d • Remote

About The Position

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 100 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 Bank Customer Protection Debit & Claims Data Science team builds the machine learning models that help our customers spend safely and get back on track if an issue does occur with their payments. Within the Agentic Claims area of this team, we are building solutions that drive down customer and contact center effort to correct payment issues while simultaneously resolving those challenges faster than ever. The team brings a variety of techniques to bear on these challenges, including agentic workflows, representation learning, and gradient boosting machines, to provide the intelligence that powers our real-time decision systems. By improving our claims resolution process we will also identify stronger leading indicators that the transaction fraud prevention side of the team to prevent more fraud and disputes.

Role Description
This role sits at the intersection of leadership and hands-on innovation, driving the transformation of claims management within the bank. You will lead cross-functional initiatives, balancing competing priorities across broad partnerships to deliver outsized impact. Success requires influencing stakeholders to adopt new techniques and expanding our solution set. While you will provide strategic oversight and lead a small team of data scientists to support the claims landscape, you will also remain deeply hands-on—personally conducting data exploration, model development, and owning the end-to-end lifecycle of solution deployment. Beyond immediate claims management innovations, you will play a pivotal role in establishing the datasets, tools, and evaluation protocols that will serve as the foundation for broader Enterprise AI developments in this space.

In this role, you will:
Partner with a cross-functional team of data scientists, software engineers, applied researchers, analysts, and product managers to deliver products customers love
Leverage a broad stack of technologies — LLMs, LangChain, Python, Ray, Spark, AWS, and more — to operationalize 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
Lead individual contributors by seeking to remove ambiguity and working closely with partners to shape the roadmap of the space

Requirements

• 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 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

Nice To Haves

• PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics
• At least 1 year of experience working with AWS
• At least 1 year of experience building agentic workflows
• At least 1 year of experience managing people
• At least 5 years’ experience in Python for large scale data analysis
• At least 5 years’ experience with machine learning

Responsibilities

• Partner with a cross-functional team of data scientists, software engineers, applied researchers, analysts, and product managers to deliver products customers love
• Leverage a broad stack of technologies — LLMs, LangChain, Python, Ray, Spark, AWS, and more — to operationalize 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
• Lead individual contributors by seeking to remove ambiguity and working closely with partners to shape the roadmap of the space

Benefits

• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
• performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior