This role pays less than
93%
of similar roles. Most pay
$174,250–$228,962
— the shaded band above.
At the midpoint, this role pays about
$145k
versus about
$202k
for comparable roles.
Based on 240 similar postings.
Employer
About Ally Financial
Ally Financial is a US-based digital financial services company offering online banking, auto financing, mortgage, and investment products. It is one of the largest all-digital banks in the United States.
Ally Financial currently has
13 open roles
on FindRole.
Listed pay typically runs
$110,000–$180,000
across 13 roles with salary data.
Principal – Data Science
As a member of the Auto Finance team within the Technology and Digital organization, you will conduct complex analytics projects, studies, and experiments to drive business strategy related to Servicing. You will transform ambiguous questions into data-driven solutions, build robust and scalable models, and develop high-quality data assets such as feature stores and actionable dashboards. The role involves productionizing analytics pipelines, performing rigorous model validation for stability and fairness, and mentoring other professionals through code reviews. To succeed, you must possess expertise in SQL, Python, R, or SAS, along with experience in machine learning algorithms, AWS cloud development tools, and Git source control. You will solve complex problems within the financial services domain, specifically focusing on data-driven decision-making to improve customer experiences and internal business outcomes through advanced statistical modeling and experiment design.
Translate ambiguous business questions into data-driven solutions and actionable insights for leadership.
Design, execute, and interpret experiments to evaluate business strategy changes and quantify impact.
Build robust, scalable models and automated monitoring systems aligned with Model Risk Management standards.
Develop reliable data pipelines and curated features from enterprise sources to support analysis and model development.
Create high-quality data assets including feature stores, standardized metrics, and actionable dashboards.
Produce production-ready analytics pipelines in collaboration with data and implementation teams.
Manage end-to-end project delivery by defining problem statements, creating plans, and managing risks.
Mentor other professionals through code reviews and knowledge sharing to promote best practices in modeling.
What we're looking for
7+ years of relevant experience.
Bachelor's degree in a quantitative or technical discipline (Math, Computer Science, Data Science/Analytics, Applied Statistics) or equivalent practical experience.
Significant experience (5+ years) in analytics, data science, machine learning, or applied statistics with a track record of delivering production-impacting work (preferred).
Master's degree in a quantitative or technical discipline (preferred).
Domain experience in financial services, specifically auto lending, credit risk, pricing, fraud, or portfolio optimization (preferred).
Strong working knowledge of machine learning algorithms, AWS and cloud development tools, and Data Science/Analytics/BI methodologies (preferred).
Advanced skills in SQL, Python, and statistical model development; R or SAS is a plus (preferred).
Experience with Git/source control including branching, pull requests, and code reviews (preferred).