Senior Manager, Data Science - LLM Customization Team

Capital One • San Jose, CA

2d

About The Position

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.

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.

Requirements

• Bachelor’s Degree plus 7 years of experience in data analytics, or Master’s Degree plus 5 years of experience in data analytics, or PhD plus 2 years of experience in data analytics
• At least 3 years’ experience in open source programming languages for large scale data analysis
• At least 3 years’ experience with machine learning
• At least 3 years’ experience with 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
• 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.
• 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.
• 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.
• An engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes.
• Experience in delivering libraries, platforms, or solution level code to existing products.

Responsibilities

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

Benefits

• comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being
• performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI)

What This Job Offers

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