Senior Associate, Data Science

Capital One Financial

Confirmed live today Low trust

Quick summary

Work type: On-site
Location: McLean, VARichmond, VA
Salary: $135,600–$154,800 / yr
Employment: Full-time
Posted: 67 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $176k

This role $145k

$123k $223k

below market most similar roles pay here above market

This role pays less than 68% of similar roles. Most pay $139,875–$211,750 — the blue band above. At the midpoint, this role pays about $145k versus about $176k 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 2107 open roles on FindRole.

Listed pay typically runs $197,300–$225,100 across 1107 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

The Senior Associate, Data Science joins the Credit Risk Management, Loss Forecasting and Allowance team to forecast and optimize future losses associated with the credit card portfolio. In this role, you will partner with cross-functional teams of data scientists, software engineers, and product managers to identify and quantify model risks. You will build statistical and machine learning models to challenge existing production models, contribute to model governance, and automate insight generation. Your daily work involves data transformation and supporting card loss forecasting for resilience, outlook, allowance, and CCAR. You will utilize a technical stack including Python, Conda, AWS, Spark, Scala, R, and SQL. The position requires a quantitative background to solve complex problems involving big data structures and large-scale customer records to improve financial outcomes.

Skills

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

What you'll do

Identify and quantify risks associated with credit card portfolio models.
Use Python, Conda, AWS, and Spark to extract insights from large datasets.
Build statistical and machine learning models to challenge existing production models.
Contribute to the model governance of next-generation machine learning systems.
Present model risk impacts and findings to executive leadership.
Support card loss forecasting for resilience, outlook, allowance, and CCAR.
Automate insight generation through partnerships with software engineering and product teams.

What we're looking for

Must have a Bachelor's degree in a quantitative field plus 2 years of data analytics experience.
Must have a Master's degree in a quantitative field or an MBA with a quantitative concentration.
Must have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.
Must have experience building, validating, and backtesting statistical and machine learning models.
Must have the skills to retrieve, combine, and analyze data from a variety of sources and structures.
Master’s degree in a STEM field or a PhD in a STEM field (preferred).
At least 2 years of experience in Python, Scala, or R (preferred).
At least 2 years of experience with machine learning and SQL (preferred).

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