Director of Predictive Modeling & ML for Risk

Credit Acceptance; United States; On-site; USD 158,000 - 170,000; Full time

Benefits offered by this job

401(K) match

Adoption assistance

Parental leave

Tuition reimbursement

Comprehensive medical/dental/vision

Job summary

Credit Acceptance is seeking a senior data scientist to lead predictive modeling efforts across credit risk, collections, and operations. The role combines remote work with occasional travel to our Southfield, Michigan office, and requires strong collaboration with cross-functional teams.

You will mentor junior data scientists, promote modern data science tools, and present insights to executives. A deep ML toolkit and governance mindset are essential, with a focus on delivering impact.

Qualifications

• Bachelor's degree in a quantitative discipline.
• 5+ years in predictive modeling and analytics.
• 5+ years applying ML in production environments.
• Strong cross-functional leadership and stakeholder management.
• Advanced Python, SQL, and statistical tools (R, SAS).

Responsibilities

• Lead design and deployment of predictive models for credit risk, collections, and operations.
• Integrate advanced ML techniques (ensemble models, deep learning, NLP).
• Mentor and support junior and peer-level data scientists.
• Promote adoption of modern data science tools and platforms.
• Present insights to senior and cross-functional stakeholders.
• Drive experimentation with emerging techniques (causal inference, GenAI).

Skills

Python

SQL

R

SAS

Leadership

Communication

Education

Bachelor's degree in quantitative discipline

Master's or PhD in quantitative discipline

Job description

Credit Acceptance is seeking a senior data scientist to lead predictive modeling efforts across credit risk, collections, and operations. The role combines remote work with occasional travel to our Southfield, Michigan office, and requires strong collaboration with cross-functional teams.

You will mentor junior data scientists, promote modern data science tools, and present insights to executives. A deep ML toolkit and governance mindset are essential, with a focus on delivering impact.