Senior Manager, Data Scientist - Applied AI

Capital One • McLean, VA

1d

About The Position

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 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 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 the driving force behind AI in Payments, architecting custom 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. You will work with a seasoned group of AI/ML specialists, experimenting with emerging technologies in Generative AI to bridge the gap between world-class research and real-world production. As a key member of this team, you will contribute to the global AI community while delivering the software that powers the future of the global payments ecosystem. 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 the insights hidden within huge 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. Flex your interpersonal skills to 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, 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 or large computer vision 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.

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 managing people
• At least 5 years’ experience in Python, Scala, or R 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, 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 the insights hidden within huge 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.
• Flex your interpersonal skills to translate the complexity of your work—including model explainability and architectural trade-offs—into tangible business goals.

What This Job Offers

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