Credit Acceptance

Director, Predictive Modeling and Machine Learning

United States full-time Executive $205,561 - $301,490
full-time Executive level Technology & IT Salary listed Curated
Sign in to apply Free account — we bring you straight back to this role.

About the role

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 Director is a strategic, senior-level individual contributor who defines and drives the modeling strategy across credit risk, servicing, and collections. This role combines deep technical expertise with business acumen and cross-functional influence. While not initially a people manager, the Director may lead initiatives and mentor others, with potential to transition into formal leadership.Outcomes and Activities

Define and execute the strategic roadmap for predictive modeling and machine learning

Lead cross-functional initiatives integrating analytics into business processes

Oversee development, deployment, and monitoring of high-impact models

Serve as a strategic advisor to senior leadership on data strategy and innovation

Represent Predictive Analytics in regulatory, audit, and governance forums

Foster partnerships across the organization

Requirement:

Bachelor's in a quantitative discipline

10+ years of experience in predictive modeling and machine learning

6+ years of experience leading strategic initiatives or mentoring senior-level peers

Deep expertise in credit risk modeling and ML techniques

Advanced proficiency in Python, SQL, and statistical tools (e.g., R, SAS)

Strong understanding of cloud architecture and model lifecycle management

Proven ability to influence senior stakeholders

Experience with regulatory compliance in financial services

Preferred:

Ph.D. or Master’s in a quantitative discipline

Experience in auto finance or consumer lending

Expertise with cloud platforms (AWS, Azure, GCP, etc.) and MLOps tools (MLflow, Kubeflow, etc.)

Target Compensation: $205,561 – $301,490 base salary + annual bonus
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.
#zip
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.
Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Executive
Technology & IT Business Development Data Analysis Finance MySQL Python Executive level

Likely questions

  1. Tell us about work you have done that is close to the Director, Predictive Modeling and Machine Learning role.
  2. How would you approach your first 30 days at Credit Acceptance?
  3. Which of Business Development, Data Analysis and Finance have you used recently, and what did it help you achieve?
  4. How have you led people, improved a process, or made a hard decision in a previous role?
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with Business Development, Data Analysis and Finance.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the Director, Predictive Modeling and Machine Learning role because I can bring practical experience in Business Development, Data Analysis and Finance, learn the team quickly, and contribute to the outcomes Credit Acceptance needs from this hire.

Related jobs.

More roles from this company or category.