Manager Data Science - Global Payment Network AI Foundations
Team Description
The Global Network Analytics (GNA) team—specifically within our Foundational AI & Automation pillar—builds machine learning engines and AI agents to drive foundational, scalable intelligence across the payments ecosystem. We create core models and AI tools to power merchant intelligence, acceptance growth, fraud/risk decisioning, and enterprise automation.
In this role, you will:
- Partner with a cross-functional team of data scientists, software engineers, ML engineers, and product managers to deliver AI-powered capabilities that evaluate billions of network transactions and transform merchant intelligence.
- Leverage a modern tech stack—PyTorch, AWS, VectorDBs, and LLMs—to extract actionable insights from complex numerical, tabular, and textual data feeds.
- Serve as the domain expert in Natural Language Processing (NLP) and Large Language Models (LLMs), adapting, fine-tuning, and working with technology to deploy them for business users.
- Translate technical ML complexity into tangible business value and strategic goals.
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 advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms.
- Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences.
- You are experienced in training language models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF.
- You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products.
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 6 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 4 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 1 year of experience performing data analytics
- At least 1 year of experience leveraging open source programming languages for large scale data analysis
- At least 1 year of experience working with machine learning
- At least 1 year of experience utilizing relational databases
Preferred Qualifications:
- PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in model development
- At least 4 years’ experience in Python, Scala, or R
- At least 4 years’ experience with machine learning
- At least 4 years’ experience with SQL
- Experience with Large Language Models (LLMs), including utilizing embedding models and working with vector databases
- Experience designing and implementing AI workflows and autonomous AI agents
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.
Richmond, VA: $179,400 - $204,700 for Mgr, Data ScienceNew York, NY: $215,200 - $245,600 for Mgr, Data Science
Riverwoods, IL: $179,400 - $204,700 for Mgr, Data Science
Chicago, IL: $179,400 - $204,700 for 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.
This role is expected to accept applications for a minimum of 5 business days.