Senior Associate, Data Science

Capital One Financial

Confirmed live yesterday Trusted

Quick summary

Work type
On-site
Location
McLean, VARichmond, VA
Salary
$135,600–$154,800 / yr
Posted
21 days ago
Freshness
Confirmed live yesterday
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $181k
This role $145k
$125k most similar roles pay here $236k

This role pays less than 76% of similar roles. Most pay $146,825–$215,612 — the shaded band above. At the midpoint, this role pays about $145k versus about $181k 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 998 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 992 roles with salary data.

Most-posted roles

View all roles at Capital One Financial

At a glance

TL;DR · Senior Associate, Data Science

Role Posting Log in to save

As a Senior Associate, Data Science, you will join the Credit Risk Management, Loss Forecasting and Allowance team to modernize loss forecasting and perform data transformation. You will collaborate with cross-functional teams of engineers and product managers to identify model risks, build statistical and machine learning models to challenge existing production systems, and contribute to the governance of next-generation models. The role involves uncovering insights within large datasets to support card loss forecasting, resilience, outlook, allowance, and CCAR requirements. You will utilize a technical stack including Python, Conda, AWS, Spark, SQL, Scala, and R to analyze complex data structures. This position addresses the critical business problem of forecasting and optimizing future losses associated with the credit card portfolio while ensuring robust model performance in a high-scale environment.

Skills

Python AWS Spark SQL Machine Learning Conda Scala R Statistical Modeling Big Data Data Transformation Model Governance

What you'll do

  • Identify and quantify risks associated with credit card portfolio models in collaboration with cross-functional teams.
  • Use Python, Spark, and AWS to extract insights from large-scale datasets.
  • Build statistical and machine learning models to challenge current production "champion" models.
  • Support the modernization of loss forecasting for resilience, outlook, allowance, and CCAR reporting.
  • Manage the governance of next-generation machine learning models.
  • Present complex model risks and their potential business impacts to executive leadership.

What we're looking for

  • A Bachelor's degree in a quantitative field plus 2 years of experience performing data analytics.
  • A Master's degree in a quantitative field or an MBA with a quantitative concentration.
  • At least 2 years of experience with Python, Scala, or R.
  • At least 2 years of experience with machine learning.
  • At least 2 years of experience with SQL.
  • Experience working with AWS and other cloud computing platforms.
  • Proficiency in building, validating, and backtesting statistical and machine learning models.
  • Ability to retrieve, combine, and analyze large datasets from various sources and structures.

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