Senior Manager, Data Science - AI Foundations

Capital One Capital One · Banking · New York, NY +2

Senior Manager, Data Science - AI Foundations role at Capital One, focusing on building and shipping AI/ML solutions for their mobile app. The role involves partnering with cross-functional teams, leveraging technologies like PyTorch, AWS, Hugging Face, LangChain, and VectorDBs, and specializing in NLP and LLMs for customer-facing applications. Responsibilities include model development from design to production, operationalization, and translating complex work into business goals. The ideal candidate is customer-first, innovative, creative, a leader, technical with hands-on LLM experience, and influential. Experience in training language models, computer vision models, and expertise in areas like training optimization, self-supervised learning, explainability, and RLHF is required, along with a track record of delivering models at scale in both training and inference.

What you'd actually do

  1. 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.
  2. 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 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 customer facing applications and features.
  4. Build machine learning and 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 that serve 80+ million customers.
  5. Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Skills

Required

  • Bachelor's Degree in a quantitative field plus 7 years of experience performing data analytics OR Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 5 years of experience performing data analytics OR PhD in a 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
  • experience in training language models or large computer vision models
  • expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF
  • 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

Nice to have

  • PhD in “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

What the JD emphasized

  • building and shipping state of the art scalable architecture, AI/ML solutions
  • operationalize them in scalable and resilient production systems
  • delivering models at scale both in training data and inference volumes
  • track record of delivering models at scale both in training data and inference volumes

Other signals

  • building and shipping state of the art scalable architecture, AI/ML solutions
  • delivering models at scale both in training data and inference volumes
  • operationalize them in scalable and resilient production systems