Senior Analyst, Predictive Analytics and Machine Learning at Credit Acceptance Careers – USA - Remote | Jobyssey

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.

Our Engineering and Analytics Team Members utilize the latest technology to develop, monitor, and maintain complex practices that help optimize our success. Our Team Members value being challenged, are encouraged to express their ideas, and have the flexibility to enjoy work life balance. We build intrinsic value by partnering with all functions of our business to support their success and make strategic business decisions. We focus on professional development and continuous improvement while enjoying a casual work environment and Great Place to Work culture!

The Senior Analyst, Predictive Analytics and Machine Learning designs, develops, and maintains statistical and machine learning models that support high‑impact business decisions across pricing, credit risk, and other areas. This role is a hands‑on, advanced individual contributor position focused on rigorous analysis, model development, and production performance monitoring, with strong partnership across business and technical stakeholders.

Outcomes and Activities:

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.

Requirements:

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.

Preferred:

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.

Targeted Compensation: $128,000 - $165,000 base salary + an annual bonus plan

This position is not currently open to individuals who require sponsorship now or in the future to work legally for Credit Acceptance, such as H-1b / H-4 or F-1 OPT visa holders.

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Benefits

Excellent benefits package that includes 401(K) match, adoption assistance, parental leave, tuition reimbursement, comprehensive medical/ dental/vision and many nonstandard benefits that make us a Great Place to Work

Our Company Values:

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

Expectations:

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

Advice!

We understand that your career search may look different than others. Our hiring team wants to make sure that this would be a fit not just for us, but for you long term. If you are actively looking or starting to explore new opportunities, send us your application!

P.S.

We have great details around our stats, success, history and more. We’re proud of our culture and are happy to share why – let’s talk!

Required degrees must have been earned at institutions of Higher Education which are accredited by the Council for Higher Education Accreditation or equivalent.

Credit Acceptance is dedicated to providing a safe and inclusive working environment for all. As part of our Culture of Compliance, we are proud to be an Equal Opportunity Employer and value our culturally diverse workforce. All qualified applicants will receive consideration for employment regardless of the person’s age, race, color, religion, sex, gender, sexual orientation, gender identity, national origin, veteran or disability status, criminal history, or any other legally protected characteristic.

California Residents: Please click here for the California Consumer Privacy Act (CCPA) notice regarding the personal information Credit Acceptance may collect from you.

Play the video below to learn more about our Company culture.

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Outcomes and Activities:

Requirements:

Preferred: