Remote Senior Manager, Predictive Modeling & ML

creditacceptance; United States; Remote; USD 158,000 - 170,000; Full time

Benefits offered by this job

401K match

Parental leave

Tuition reimbursement

Medical coverage

Dental coverage

Vision coverage

Job summary

Credit Acceptance seeks a seasoned Manager of Predictive Modeling & Machine Learning to lead development and deployment of models guiding credit risk, collections, and operations. The role blends traditional predictive modeling with modern ML and MLOps, requiring hands-on expertise and strategic business acumen.

The ideal candidate will mentor data scientists, drive adoption of advanced analytics, and present insights to stakeholders, with strong Python/SQL skills and a proven leadership record.

Qualifications

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

Responsibilities

• Lead the design and deployment of predictive models for credit risk, collections, and operations.
• Integrate advanced ML techniques (e.g., 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 (e.g., causal inference, GenAI).

Skills

Predictive modeling

Machine Learning

Leadership

Communication

Cross-functional collaboration

Data analysis

Education

Bachelor's degree in quantitative discipline

Ph.D or Master’s in quantitative discipline

Tools

Python

SQL

R

SAS

Job description

Credit Acceptance seeks a seasoned Manager of Predictive Modeling & Machine Learning to lead development and deployment of models guiding credit risk, collections, and operations. The role blends traditional predictive modeling with modern ML and MLOps, requiring hands-on expertise and strategic business acumen.

The ideal candidate will mentor data scientists, drive adoption of advanced analytics, and present insights to stakeholders, with strong Python/SQL skills and a proven leadership record.