Senior Manager, Data Scientist - Bank Customer Protection Agentic Claims

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

• 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.
• 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.
• 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.
• 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., * 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, * 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 *

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.

McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science

New York, NY: $250,800 - $286,200 for Sr Mgr, 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.

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., 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).