Principal Data Scientist - LLM Customization Team - Capital One National Association

Center 3 (19075), United States of America, McLean, Virginia

Principal Data Scientist - LLM Customization Team

At Capital One, we think big and do big things. We are not just a nationally recognized credit card issuer, a top 10 bank by deposit, but a high-tech company with products that reach tens of millions of consumers and have been recognized by numerous prestigious awards for their customer-friendliness. Capital One was the first major bank to move to cloud computing and to publish APIs for the Open Banking future. AI is transforming every industry. At Capital One, you will help shape how it transforms financial services.

Team Description

The AI Foundations LLM Customization team is at the center of bringing our vision for LLMs and GenAI at Capital One to life. Our work touches every aspect of the research life cycle, from research to building production systems. We work with product, technology, and business leaders to apply the state of the art in AI to our business. You will be the driving force to experiment, innovate, and create next generation experiences powered by the latest emerging generative AI technologies.

In this role, you will:

1. Partner with a cross-functional team of data scientists, applied researchers, software engineers, machine learning engineers, and product managers to deliver AI powered products that change how customers interact with their money.

2. Leverage a broad stack of technologies — Pytorch, Hugging Face, AWS Ultraclusters, LangChain, VectorDBs, and more — to reveal the insights hidden within huge volumes of numeric and textual data.

3. Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for business specific applications and features.

4. Build NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems.

5. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

The Ideal Candidate is:

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

6. 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:

1. Currently has, or is in the process of obtaining a Bachelor’s Degree plus 5 years of experience in data analytics, or currently has, or is in the process of obtaining a Master’s Degree plus 3 years in data analytics, or currently has, or is in the process of obtaining PhD, with an expectation that required degree will be obtained on or before the scheduled start date.

2. At least 1 year of experience in open source programming languages for large scale data analysis.

3. At least 1 year of experience with machine learning.

Preferred Qualifications:

1. Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics) plus 3 years of experience in data analytics, or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics).

2. At least 1 year of experience working with AWS.

3. At least 3 years’ experience in Python, Scala, or R.

4. At least 3 years’ experience with machine learning.

5. At least 3 years’ experience with SQL.

6. At least 1 year of experience with relational databases.

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.

New York City (Hybrid On-Site):
$165,100 - $188,500 for Data Science PhD

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. No agencies please. Capital One is an equal opportunity employer committed to diversity and inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to sex (including pregnancy, childbirth or related medical conditions), race, color, age, national origin, religion, disability, genetic information, marital status, sexual orientation, gender identity, gender reassignment, citizenship, immigration status, protected veteran status, or any other basis prohibited under applicable federal, state or local law.