Overview
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 / Role Description
AI Foundations Specialist Models Data Science team builds and ships state of the art scalable architecture, AI/ML solutions for Capital One’s award-winning mobile app. We partner with product, tech and design teams to deliver app features that delight customers with dynamic and personalized experiences, enable them to chat with Capital One’s digital assistant Eno, or search for useful contents. You will be the driving force to experiment, innovate and create next generation experiences powered by the latest emerging generative AI technologies.
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, Hugging Face, LangChain, Lightning, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.
- Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features.
- Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partner with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers.
- Translate the complexity of your work into tangible business goals.
The Ideal Candidate
- Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. It’s about making the right decision for our customers.
- Innovative. You continually research and evaluate emerging technologies and stay current on state-of-the-art methods, technologies, and applications.
- Creative. You thrive on defining and solving big, undefined problems and aren’t afraid to share a new idea.
- Leader. You challenge conventional thinking and work with stakeholders to improve the status quo; focused on talent development for your team and beyond.
- Technical. You’re comfortable with advanced ML and DL technologies including language models and have hands-on experience with LLMs and open-source tools and cloud platforms.
- Influential. You can bring along a cross-functional team in breakthrough innovations and communicate findings to non-technical audiences.
- Experience in training language models or large computer vision models, with expertise in subdomains such as training optimization, self-supervised learning, explainability, RLHF.
- Engineering mindset with a track record of delivering models at scale, including training data and inference, and delivering libraries, platforms, or solution-level code to products.
Basic Qualifications
- Currently has, or is in the process of obtaining one of the following with the expectation that the degree will be obtained by start date: a) Bachelor’s in a quantitative field plus 7 years of data analytics experience; b) Master’s in a quantitative field or MBA with quantitative concentration plus 5 years of data analytics; c) PhD in a quantitative field plus 2 years of 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
Preferred Qualifications
- PhD in a STEM field
- Experience working with AWS
- At least 5 years’ experience in Python, Scala, or R
- At least 5 years’ experience with machine learning
- At least 5 years’ experience with SQL
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. Salaries for part-time roles will be prorated. Locations and ranges: McLean, VA: $225,400 - $257,200; New York, NY: $245,900 - $280,600; San Jose, CA: $245,900 - $280,600. Other locations follow local pay ranges. This role may earn incentive compensation (cash and/or long-term incentives).
Capital One offers a comprehensive set of health, financial and other benefits. Eligibility varies by status and level. This role is expected to accept applications for a minimum of 5 business days.
No agencies. Capital One is an equal opportunity employer (EOE, including disability/vet). Capital One complies with applicable laws on criminal background inquiries where required. For accommodations, contact For recruiting process questions, email Capital One does not endorse third-party products or services. Some positions posted outside the United States may be for local entities (e.g., Capital One Canada, Capital One Europe, COPSSC).
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