Senior Data Science & AI Leader - NLP, ML at Scale

Capital One; Richmond (VA); On-site; USD 209,000 - 239,000; Full time

Job summary

Capital One is seeking a Data Scientist to advance AI-powered products across payments and risk, leveraging NLP and ML at scale. You will collaborate with data scientists, software engineers, and product managers to deploy models that impact billions of interactions and help customers save time and money.

You will work with PyTorch, AWS, Hugging Face, and related tools to build and operationalize models for production across 80+ million customers.

Qualifications

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

Responsibilities

• Partner with cross-functional teams to deliver AI-powered products affecting customer interactions with money.
• Leverage technologies such as PyTorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs to extract insights from large datasets.
• Be the NLP expert to harness Large Language Models for customer-facing applications and features.
• Build ML and NLP models through design, training, evaluation, and validation and deploy them in scalable production systems serving 80+ million customers.
• Translate complex work into tangible business goals.

Skills

Open source languages

Machine learning

Relational databases

Education

Bachelor's degree in quantitative field

Master's degree in quantitative field or MBA with quantitative concentration

PhD in quantitative field

Tools

PyTorch

Hugging Face

AWS

Job description

Capital One is seeking a Data Scientist to advance AI-powered products across payments and risk, leveraging NLP and ML at scale. You will collaborate with data scientists, software engineers, and product managers to deploy models that impact billions of interactions and help customers save time and money.

You will work with PyTorch, AWS, Hugging Face, and related tools to build and operationalize models for production across 80+ million customers.