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 $146,693–$214,850 — 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

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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, automate insight generation, and build statistical or machine learning models to challenge existing production systems. Your daily work involves managing card loss forecasting for resilience, outlook, allowance, and CCAR requirements. To succeed in this role, you must be proficient in a technical stack including Python, Conda, AWS, Spark, SQL, Scala, and R. You will utilize these tools to analyze large datasets and develop innovative solutions for the credit card portfolio. The role requires a statistically-minded professional capable of building, validating, and backtesting models while communicating complex risks to executive leadership.

Skills

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

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 existing production "champion" models.
Support the modernization of loss forecasting for resilience, outlook, allowance, and CCAR requirements.
Manage the governance of next-generation machine learning models.
Present model risk impacts and data insights to executive leadership.
Research and evaluate emerging technologies to improve internal data science solutions.

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 cloud computing platforms.
Ability to build, validate, and backtest statistical and machine learning models.
Proficiency in retrieving, combining, and analyzing data from various sources and structures.

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