Principal Associate Data Scientist, AI in Credit

Capital One Financial

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Quick summary

Work type
On-site
Location
McLean, VANew York, NYRichmond, VA
Employment
Full-time
Posted
62 days ago
Freshness
Confirmed live today
Nearby
99+ roles within 25 mi

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Salary context

How this pay compares to similar roles

Similar $190k
$137k $244k
below market most similar roles pay here above market

This listing doesn't post a salary. Most similar roles pay $159,750–$220,000.

Based on 240 similar postings.

Employer

About Capital One Financial

Capital One Financial is a bank holding company specializing in credit cards, auto loans, banking, and savings products, known for its data-driven approach to consumer and commercial finance. Industry: Financial Services & Banking

Capital One Financial currently has 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 roles with salary data.

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At a glance

TL;DR · Principal Associate Data Scientist, AI in Credit

Role Posting Log in to save

Principal Associate, Data Scientist - AI in Credit joins the AI in Credit team within the US Card Intelligence Segments organization. This role involves developing modeling approaches to forecast credit outcomes in a rapidly changing economic environment and building frameworks for AI-model-based decisioning in a highly regulated industry. The individual will apply cutting-edge explainability techniques to identify insights from complex models while collaborating with a cross-functional team of engineers and analysts. Required skills include experience with clustering, classification, sentiment analysis, time series, and deep learning. The candidate should possess proficiency in Python, Scala, or R, along with machine learning expertise and distributed computing knowledge. The work focuses on developing the next generation of predictive models to forecast how customers use credit cards.

What does a Data Scientist earn in Virginia?

Median $162000 from 89 postings across 9 companies.

See salary data

Skills

Machine Learning Python Scala R Deep Learning Distributed Computing Statistical Modeling Time Series Clustering Classification Sentiment Analysis Big Data High Performance Computing ROC Curve Confusion Matrix

What you'll do

  • Develop modeling approaches to forecast credit outcomes in a rapidly changing economic environment.
  • Apply cutting-edge explainability techniques to identify insights from complex models.
  • Develop frameworks for AI-model-based decisioning in a highly regulated industry.
  • Retrieve, combine, and analyze data from a variety of sources and structures.
  • Build, validate, and backtest models using clustering, classification, time series, and deep learning.
  • Research and evaluate emerging technologies and state-of-the-art methods for practical application.

What we're looking for

  • A Bachelor's Degree in a quantitative field plus 5 years of experience performing data analytics.
  • A Master's Degree in a quantitative field or an MBA with a quantitative concentration plus 3 years of experience performing data analytics.
  • A PhD in a quantitative field.
  • Experience with clustering, classification, sentiment analysis, time series, and deep learning.
  • Experience in explainability (preferred).
  • Experience with distributed computing (preferred).
  • At least 3 years’ experience in Python, Scala, or R (preferred).
  • At least 3 years’ experience with machine learning (preferred).

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