Senior Data Science Manager - AI Foundations & NLP

Capital One

McLean (VA)

Vor Ort

USD 230.000 - 262.000

Vollzeit

14 Tage+

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Zusammenfassung

Capital One seeks a Senior Manager, Data Science - AI Foundations to lead a cross-functional team building foundational AI capabilities across payments, fraud, risk, and customer insights. You will ship NLP and ML models at scale using PyTorch, AWS, and open-source tools, serving millions of customers.

The ideal candidate blends vision with hands-on expertise in training LLMs, self-supervised learning, and explainability, and excels at communicating results to non-technical partners while

Qualifikationen

  • Bachelor's degree in a quantitative field plus 7 years analytics
  • Master's degree or MBA with quantitative concentration plus 5 years analytics
  • PhD in a quantitative field plus 2 years 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

Aufgaben

  • Partner with cross-functional teams to deliver AI-powered products.
  • Leverage PyTorch, AWS Ultraclusters, Hugging Face, LangChain, and more to extract insights from large data volumes.
  • Be the NLP expert to harness Large Language Models for customer-facing features.
  • Build ML and NLP models from design through training, evaluation, and validation; collaborate with engineering to productionize.
  • Translate complex work into tangible business goals.

Kenntnisse

Python
Scala
R
NLP
ML

Ausbildung

Bachelor's degree
Master's degree
PhD

Tools

PyTorch
Hugging Face
LangChain
Lightning
VectorDBs
AWS

Jobbeschreibung

Capital One seeks a Senior Manager, Data Science - AI Foundations to lead a cross-functional team building foundational AI capabilities across payments, fraud, risk, and customer insights. You will ship NLP and ML models at scale using PyTorch, AWS, and open-source tools, serving millions of customers.

The ideal candidate blends vision with hands-on expertise in training LLMs, self-supervised learning, and explainability, and excels at communicating results to non-technical partners while

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