Senior Analyst, Predictive Analytics and Machine Learning

Credit Acceptance is proud to be an award-winning company recognized both locally and nationally across multiple workplace categories. Our world-class culture is shaped by dedicated team members who are driven to succeed as professionals individually and together as a team. Backed by a strong product, exceptional people, and a stable financial foundation, we’ve grown into a leading provider of used and new car financing across the country.

• This position will work from home; occasional planned travel to our Southfield, Michigan office may be required.  However, this position is permitted to work at our Southfield, Michigan office if requested by the team member.
• Develop and maintain complex statistical and machine learning models that optimize high‑volume, data‑driven decisions and deliver measurable business value.
• Actively monitor models in production, identify performance degradation or data issues, and recommend corrective actions or enhancements.
• Develop complex SQL and analytical code to extract, transform, and validate large, multi‑source datasets used for modeling, reporting, and decision support.
• Perform ad hoc and exploratory analyses to address business questions, evaluate trade‑offs, and inform policy or strategy decisions.
• Translate high‑level business objectives into analytical tasks, technical specifications, and modeling approaches.
• Ensure data quality, consistency, and suitability for modeling; support testing, validation, and implementation activities required for production deployment.

• Bachelor’s degree or higher in a quantitative field (e.g., statistics, mathematics, economics, engineering, computer science, or related discipline).
• 3+ years of experience applying analytical and programming skills in a business or research environment.
• Proficiency in one or more analytical and programming languages such as Python, SQL, R, or SAS.
• Strong analytical problem‑solving skills with the ability to apply quantitative methods creatively to business problems.
• Expertise in extracting, manipulating, and analyzing large‑scale datasets.

• Advanced proficiency in Python, SQL, and statistical tools (e.g., R, SAS).
• Experience developing or supporting predictive models such as credit scorecards, pricing models, or collections strategies.
• Experience in financial services analytics or a related regulated, data‑intensive industry.
• Familiarity with model performance monitoring, validation concepts, and production analytics.

To be successful in this role, Team Members need to be:

• Positive by maintaining resiliency and focusing on solutions
• Respectful by collaborating and actively listening
• Insightful by cultivating innovation, accumulating business and role specific knowledge, demonstrating self-awareness and making quality decisions
• Direct by effectively communicating and conveying courage
• Earnest by taking accountability, applying feedback and effectively planning and priority setting

• Remain compliant with our policies processes and legal guidelines
• All other duties as assigned
• Attendance as required by department