Financial Data Scientist

US Bank

Hybrid

Quick summary

Work type
Hybrid
Location
Atlanta, GA
Salary
$111,605–$131,300 / yr
Posted
11 days ago
Closes
Jun 20, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $157k
This role $121k
$97k most similar roles pay here $221k

This role pays less than 92% of similar roles. Most pay $126,800–$187,102 — the shaded band above. At the midpoint, this role pays about $121k versus about $157k for comparable roles.

Based on 240 similar postings.

Employer

About US Bank

U.S. Bank (U.S. Bancorp) is the fifth-largest bank in the United States, providing retail banking, corporate and commercial banking, wealth management, and payment services to millions of customers. Industry: Banking & Financial Services

US Bank currently has 44 open roles on FindRole.

Listed pay typically runs $111,605–$131,300 across 41 roles with salary data.

Most-posted roles

View all roles at US Bank

At a glance

TL;DR · Financial Data Scientist

The Financial Data Scientist role at U.S. Bank involves providing advanced financial and analytical support through mathematical modeling, forecasting, and data-driven insights. This senior-level position requires developing and maintaining complex financial models using techniques like time series analysis to forecast revenue, expenses, pricing, and volume trends. The incumbent will analyze large datasets with SQL and Python, automate analytics solutions, and collaborate closely with finance leadership to deliver actionable insights for budgeting and performance management. Essential skills include advanced degrees in quantitative fields, proficiency in Python/R/SAS/SQL, experience with machine learning techniques, and strong data analysis capabilities. This role operates within the credit card payment processing domain, requiring rigorous validation of financial data across multiple systems.

What you'll do

  • Develop and maintain financial models for forecasting and scenario analysis.
  • Apply time series modeling techniques for revenue and expense forecasting.
  • Analyze complex datasets using SQL and Python to identify trends and risks.
  • Design and automate repeatable analytics solutions for reporting purposes.
  • Translate analytical results into actionable insights for finance leadership.

What we're looking for

  • Bachelor's degree in a quantitative field or equivalent work experience
  • Advanced degree in statistics, data science, applied mathematics, etc.
  • Experience with time series analysis and forecasting techniques
  • Strong skills in Python/R/SAS/SQL for data extraction and analytics
  • Demonstrated ability to analyze complex datasets and extract meaningful insights
  • Familiarity with version control and reproducible coding workflows
  • Effective communication skills to translate analytical results into actionable insights

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