Opportunity Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list. Find me work
remoteroles

Senior Manager, Predictive Modeling and Machine Learning

Credit Acceptance customer.creditacceptance.com Open
Remote United States Full-time Senior Machine Learning Engineering

At a glance

Senior Machine Learning Engineering role at Credit Acceptance. Remote, United States · full-time · $184,354–$270,386 base.

SalaryStated by Credit Acceptance
$184,354 – $270,386
Base salary for this role, in USD per year, as published in the posting.
RoleMachine Learning Engineering
SenioritySenior
LocationUnited States
WorkplaceRemote
EmploymentFull-time
Base pay$184,354–$270,386
PostedSep 14, 2026
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Build and put predictive models into use for credit risk, collections and operations
  • Apply methods such as ensemble learning, deep learning and natural language processing to modeling work
  • Guide junior and peer data scientists and encourage use of current data science platforms
  • Share model findings with senior leaders and cross-functional partners
  • Test emerging approaches, including causal inference and generative AI

What you bring

  • A bachelor's degree in a quantitative discipline
  • At least eight years in predictive modeling and analytics, including six years putting machine learning into production
  • Advanced Python, SQL and statistical-tool skills, plus experience with cloud platforms and MLOps

Who this fits

This remote U.S. role suits a senior technical leader who can mentor colleagues, communicate with stakeholders and shape analytics decisions. Occasional planned travel to the Southfield, Michigan office may be required, and team members may choose to work there. The role may not require formal people management. Applicants who need current or future work-visa sponsorship are ineligible.

From the employer

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!

This role leads complex modeling initiatives and drives innovation in machine learning and data science. The Senior Manager designs and deploys advanced statistical and ML models that inform strategic decisions across credit risk, collections, and operations. While formal people management may not be required, the role demands strong leadership, deep technical expertise, mentorship, and business acumen to elevate the organization’s analytics capabilities.

Outcome 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.
  • 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)

Requirements:

  • Bachelor's in a quantitative field
  • 8+ years of experience in predictive modeling and analytics
  • 6+ years of experience applying ML in production environments
  • Advanced proficiency in Python, SQL, and statistical tools (e.g., R, SAS)
  • Experience with cloud platforms and MLOps tools
  • Thought leader with strong communication and stakeholder management skills

Preferred:

  • Master’s or Ph.D. in a quantitative field
  • Experience in consumer lending
  • Experience with model governance, explainability, and responsible AI

Targeted Compensation: $184,354 – $270,386 base salary + 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.

#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

To create an environment where people do their best work, we focus on the dimensions of Organizational Health. All leaders must:

  • Identify the Right People by recognizing top talent
  • Set Clear Expectations by managing change and directing others
  • Train team members and focus on developing talent
  • Performance Manage by ensuring accountability and driving results
  • Create the Right Environment by establishing trust and managing conflict
  • Maintain the Right Number of team members needed to build an effective team

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.

Opportunity

Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Machine Learning EngineeringRemote$180k+

Find me work

By the team behind remoteroles.

Find me work
Opportunity

Machine Learning Engineering work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.