Principal Associate, Data Scientist, Card Intelligence

Capital One Financial

Quick summary

Work type: On-site
Location: McLean, VANew York, NY
Salary: $161,800–$184,600 / yr
Posted: 6 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $175k

This role $173k

$125k most similar roles pay here $230k

This role pays more than 60% of similar roles. Most pay $141,975–$207,668 — the shaded band above. At the midpoint, this role pays about $173k versus about $175k for comparable roles.

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 700 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 693 roles with salary data.

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View all roles at Capital One Financial

At a glance

TL;DR · Principal Associate, Data Scientist, Card Intelligence

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As a Principal Associate, Data Scientist at Capital One’s US Card Intelligence team, you will lead the development and deployment of advanced data science models that enhance customer experiences across various stages of the credit card lifecycle. Your daily responsibilities include analyzing large datasets to uncover actionable insights, collaborating with cross-functional teams to implement machine learning solutions for marketing, acquisitions, underwriting, and fraud prevention, and continuously refining these models to optimize performance. Ideal candidates possess strong technical skills in Python or R, proficiency in SQL for data manipulation, and experience with big data technologies such as Hadoop or Spark. This role demands a deep understanding of statistical methods and the ability to translate complex analyses into practical business solutions that benefit millions of cardholders.

Skills

Python R SQL Hadoop Spark AWS Azure Git Jupyter Scikit-learn TensorFlow Keras CI/CD Docker Kubernetes PostgreSQL MongoDB

What you'll do

Develop and deploy advanced machine learning models for credit card lifecycle stages.
Analyze large datasets to drive strategic business decisions in marketing and acquisitions.
Enhance underwriting processes using sophisticated statistical methods and data science techniques.
Implement fraud prevention systems by identifying patterns and anomalies in transactional data.
Translate complex analytical insights into actionable strategies that benefit millions of customers.

What we're looking for

Minimum 5 years of experience in data science or related field.
Strong background in statistics and machine learning techniques.
Proficiency with big data technologies and tools.
Experience building predictive models for marketing, acquisitions, underwriting, and fraud prevention.
Ability to translate complex insights into actionable business strategies.

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