Senior Manager, Data Scientist - Applied AI

Overview Senior Manager, Data Scientist - Applied AI 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 to today, this data-driven approach has helped us 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 in computing and machine learning technologies to operate across billions of customer records and unlock opportunities that help everyday people save money, time and effort in their financial lives. Team Description: The Card Genesis team builds and ships state-of-the-art Gen AI models that serve as the intelligence for Capital One’s US Card business. We are driving AI in Payments, architecting solutions for time-series sequencing, natural language, and agentic reasoning at a massive scale. We partner with product, tech, and design teams to deliver next-generation applications that redefine how 80+ million customers interact with their finances. Role Description In this role, you will: Partner with a cross-functional team of data scientists, software engineers, machine learning engineers, and product managers to deliver AI-powered products that change how customers interact with their money. Leverage a broad stack of technologies—Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more—to reveal insights hidden within large volumes of numeric, textual, and sequential transaction data. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs) and Transformer-based architectures, adapting and fine-tuning them for customer-facing applications and features. Build Gen AI and Sequence models through all phases of development, from design and pre-training through evaluation and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. Translate the complexity of your work—including model explainability and architectural trade-offs—into tangible business goals. The Ideal Candidate is: Customer first. You love the process of analyzing and creating, and are focused on making the right decision for customers. Innovative. You continually research and evaluate emerging technologies and seek opportunities to apply them. Creative. You excel at defining big, undefined problems and sharing new ideas. A leader. You challenge conventional thinking and mentor others to improve the status quo. Technical. You are comfortable with advanced ML and DL technologies, have hands-on experience with LLMs and open-source tools, and work with cloud platforms. Influential. You communicate findings clearly to cross-functional teams and non-technical audiences. Experience in training language models or large computer vision models, with expertise in one or more subdomains such as training optimization, self-supervised learning, explainability, or RLHF. Engineering-minded, with a track record of delivering models at scale and providing libraries, platforms, or solution-level code to products. Basic Qualifications: Currently has, or is in the process of obtaining, one of the following with an expectation that the degree will be obtained on or before the start date: A Bachelor's Degree in a quantitative field plus 7 years of data analytics experience A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of data analytics experience A PhD in a quantitative field plus 2 years of data analytics experience 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 Preferred Qualifications: PhD in a STEM field plus 4 years of data analytics experience At least 1 year of experience working with AWS At least 1 year of experience managing people At least 5 years of experience in Python, Scala, or R for large-scale data analysis At least 5 years of experience with machine learning 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. This information is for candidates hired to work within these locations and refers to the amount Capital One is willing to pay at the time of posting. Salaries for part-time roles will be prorated based on hours. 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 for that location. The actual annualized salary offered will be reflected in the offer letter. This role is eligible for performance-based incentive compensation, which may include cash bonuses and long-term incentives (LTI). Incentives could be discretionary or non-discretionary depending on the plan. Capital One offers a comprehensive, inclusive set of health, financial and other benefits. Learn more at the Capital One Careers website. Eligibility varies based on status and 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 laws. Capital One promotes a drug-free workplace. Capital One will consider qualified applicants with criminal histories in accordance with applicable laws and policies. If you require an accommodation during the application process, please contact Capital One Recruiting at View phone number on click.appcast.io or via email at View email address on click.appcast.io. All information provided will be kept confidential and used only to provide needed accommodations. For questions about Capital One's recruiting process, please email View email address on click.appcast.io. Capital One does not provide, endorse nor guarantee third-party products or information available through this site. Capital One Financial is made up of several entities. Positions posted in Canada, the UK, or the Philippines are for Capital One Canada, Capital One Europe, and Capital One Philippines Service Corp, respectively. #J-18808-Ljbffr Capital One National Association