Senior Associate, Data Scientist - People Strategy & Analytics

Capital One Capital One · Banking · McLean, VA

This role focuses on applying AI and ML to HR talent strategy, building models for understanding associate behavior and improving HR efficiency. It involves developing NLP and ML models using prompt engineering, RAG, and evaluation frameworks, leveraging technologies like Python, SQL, AWS, LangChain, Hugging Face, and VectorDBs. The candidate will partner with cross-functional teams to deliver HR tools and AI-powered products, translating complex data science work into business outcomes.

What you'd actually do

  1. Support development of natural language processing and machine learning models through all phases, from design through training, evaluation, validation, and implementation
  2. Apply expertise in using open source large language models (LLMs) through prompt engineering, retrieval-augmented generation (RAG) and evaluation metric frameworks for business specific applications
  3. Partner with a cross-functional team of data scientists, software engineers, business analysts, and product managers to deliver industry leading HR tools and AI-powered products
  4. Leverage a broad stack of technologies — Python, SQL, AWS, LangChain, Hugging Face Transformers, VectorDBs, Pytorch/TensorFlow, and more — to reveal the insights hidden within large volumes of numeric and textual data
  5. Flex your interpersonal skills to collaborate with internal stakeholders, translating complex data science work into tangible, aligned business outcomes.

Skills

Required

  • Python
  • SQL
  • AWS
  • LangChain
  • Hugging Face Transformers
  • VectorDBs
  • Pytorch/TensorFlow
  • clustering
  • classification
  • sentiment analysis
  • time series
  • deep learning

Nice to have

  • Master’s Degree in “STEM” field
  • PhD in “STEM” field
  • experience working with AWS
  • at least 2 years’ experience in Python
  • at least 2 years’ experience with machine learning
  • at least 2 years’ experience with SQL
  • at least 1 year experience with relational databases such as Snowflake
  • at least 1 year experience with AI/ML tools and ecosystems such as Hugging Face, VectorDBs or Pytorch/TensorFlow

What the JD emphasized

  • natural language processing and machine learning models
  • prompt engineering
  • retrieval-augmented generation (RAG)
  • evaluation metric frameworks
  • HR tools and AI-powered products
  • large volumes of numeric and textual data
  • open-source languages
  • data science solutions
  • open-source tools
  • cloud computing platforms
  • built models, validated them, and backtested them
  • clustering, classification, sentiment analysis, time series, and deep learning

Other signals

  • applying analytics to talent
  • applying artificial intelligence, machine learning, and social science to build models
  • understand associate behavior
  • improve HR efficiency and tools
  • inform strategies aimed at expanding Capital One’s talent advantage
  • natural language processing and machine learning models
  • prompt engineering
  • retrieval-augmented generation (RAG)
  • evaluation metric frameworks
  • HR tools and AI-powered products
  • large volumes of numeric and textual data
  • open-source languages
  • data science solutions
  • open-source tools
  • cloud computing platforms
  • built models, validated them, and backtested them
  • clustering, classification, sentiment analysis, time series, and deep learning