Senior Analyst, Predictive Analytics and Machine Learning

Summary

Credit Acceptance is an award-winning company known for its world-class culture and dedication to professional development. The Senior Analyst, Predictive Analytics and Machine Learning will design, develop, and maintain statistical and machine learning models to support high-impact business decisions across various areas.

Responsibilities

• 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

Skills

• 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

Qualifications

Must Haves

• 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

Nice to Haves

• 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

Benefits

• 401(K) match
• Adoption assistance
• Parental leave
• Tuition reimbursement
• Comprehensive medical/ dental/vision
• Many nonstandard benefits that make us a Great Place to Work