Credit Acceptance

Role Description Put AI to work where it changes lives: We are looking for a Staff/Senior Staff Software Engineer for our Enterprise AI Enablement team. You will architect, build and ship the AI engineering systems that use state-of-the-art AI capabilities to power our entire ecosystem – solving problems for dealers, consumers and team members. You will own these systems end to end, from the first conversation with the customer through production deployment, telemetry, and ongoing improvement. Build for leverage: You will design tools, agents, and platform capabilities to be built once and adopted many times across the enterprise. Your goal is not one-off automation, but reusable foundations that enable us to solve new problems faster, with greater consistency and less duplicated effort. Outcomes and Activities: - This position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member. - Sit alongside the customers, deeply understand their workflows, locate opportunities, and translate what you learn into impactful products. - Convert ambiguous problems into production-ready solutions that are adopted across teams. - Architect, build, and deploy applied AI solutions across high-value enterprise workflows e.g. automation, document intelligence, decision support, fraud intelligence, and intelligent assistants. - Agent orchestration: Design and implement agentic orchestration systems that manage agent harnesses, context management, tool binding, reasoning steps, and business logic execution. - Knowledge retrieval: Apply modern AI retrieval architectures to index, embed, and surface relevant enterprise knowledge as a foundation for agent context. - Design and develop software and improve existing code to make it more efficient to detect bugs in the code. - Write unit-tests and validate your software against acceptance criteria. - Evolve and transform the design and architecture of applications towards leading edge technologies and practices. - Author, apply and advocate for team coding, documenting and testing standards. - Conduct impact analysis to proactively identify impact of a change across multiple applications. - Learn the business process domain to better support the business and align technologies with the business process. - Experiment and test ideas, validate assumptions against needs, reach conclusions and recommend solutions. - Lead code reviews and communicate application changes. - Document code and projects so others can easily understand, maintain and support. - Debug the problems which arise in production and propose effective solutions within the application and across multiple applications. - Read, write and review design documents. - Contribute to team's sprint commitments and actively participate in our Agile practices, including recommendations for process improvement. - Lead continuous learning activities to improve design and code quality as well as to increase application domain knowledge. - Participate in the talent selection process. - Act as a mentor to guide and review the code, designs and documentation of less experienced software engineers. Qualifications - Bachelor’s degree in Computer Science, Information Systems, or closely related field of study; or equivalent work experience. - Staff: Minimum 8 years of software engineering experience or comparable depth of experience. - Senior Staff: Minimum 10 years of software engineering experience or comparable depth of experience. - Experience in the lead role overseeing technical direction of a team of software engineering talent across multiple applications. - Strong understanding and use of one or more object-oriented programming languages and design patterns. - Practical experience in data modeling, design and messaging. - Experience working on mission-critical enterprise class applications. - High ownership and ability to operate in ambiguous environments with a strong bias for action. - Demonstrated ability to coach and mentor less experienced team members. - Willingness to participate in an on-call rotation. Requirements - Advanced understanding of IDEs, have the ability to navigate through them quickly and leverage advanced features to improve your performance. - Experience designing and building production AI retrieval systems (e.g. RAG, GraphRAG). - Experience building and shipping generative AI systems in production, at scale. - Deep expertise in operating AI systems in enterprise environments, including reliability, observability, guardrails, and compliance considerations. - Experience building context layers for agentic systems, including multi-source blending, context window management, relevance scoring, and context quality evaluation across heterogeneous data sources. - Experience with AI-oriented data architecture, including vector databases, embedding pipelines, feature stores, data contracts, and knowledge representation patterns such as ontologies and semantic layers. 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. Company Description 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.

• Prospecting automotive dealerships to enhance business development outcomes • Account management & client services to build a strategic and consultative relationship with customers • Running a territory with entrepreneurial drive and dedication similar to a small business owner

• Work closely with customers, product partners, and team members to understand workflows, clarify requirements, and translate needs into well-scoped technical deliverables. • Build applied AI capabilities across high-value enterprise workflows such as automation, document intelligence, decision support, fraud intelligence, and intelligent assistants. • Implement context-aware agentic systems that orchestrate tools, APIs, reasoning steps, and business logic using established architecture patterns • Identify when existing agents, models, APIs, or platform capabilities can be reused and contribute to practical build vs. reuse recommendations. • Stay current on practical AI engineering patterns and bring forward ideas that improve quality, speed, or customer value. • Design and develop software and improve existing code to make it more efficient to detect bugs in the code • Write unit-tests and validate your software against acceptance criteria • Author, apply and advocate for team coding, documenting and testing standards • Conduct impact analysis to proactively identify impact of a change across multiple applications • Learn the business process domain to better support the business • Experiment and test ideas, validate assumptions against needs, reach conclusions and recommend solutions • Lead code reviews and communicate application changes • Document code and projects so others can easily understand, maintain and support • Debug the problems which arise in production and propose effective solutions within the application and across multiple applications • Read, write and review design documents • Contribute to team's sprint commitments and actively participate in our Agile practices • Lead continuous learning activities to improve design and code quality as well as to increase application domain knowledge • Participate in the talent selection process • Guide and review the code, designs and documentation of less experienced software engineers

• 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 • Present insights to senior and cross-functional stakeholders

Role Description As a Senior Database Reliability Engineer, you will ensure the availability, reliability, performance, and security of enterprise database systems supporting Credit Acceptance applications. This role focuses on reducing operational toil through automation, enabling secure, scalable database platforms, and empowering engineering teams through self-service capabilities and DevOps integration. You will partner with application, infrastructure, and data teams to build and operate modern database platforms, support data replication and migration initiatives, and drive continuous improvements in reliability and efficiency. This position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member. Outcome and Activities - Platform Engineering & Automation - Design and implement automated database provisioning and configuration management - Develop Infrastructure as Code (IaC) solutions (e.g., Terraform, Ansible) - Build self-service database capabilities and platform APIs - Implement event-driven automation and auto-remediation workflows - Establish policy-driven guardrails for database configuration, access, and compliance - Integrate database services into CI/CD pipelines and release workflows - Reliability, Availability & Resilience - Define and manage Service Level Indicators (SLIs) and Service Level Objectives (SLOs) - Design and maintain high availability (HA) and disaster recovery (DR) architectures - Perform failover testing and resilience validation - Lead incident response, root cause analysis (RCA), and post-incident reviews - Drive improvements in MTTD and MTTR - Performance & Scalability Engineering - Monitor and optimize database performance, query efficiency, and throughput - Identify and resolve application-database performance bottlenecks - Design for scalability and workload isolation (replicas, partitioning, sharding) - Conduct capacity planning and forecasting - Optimize cost-performance efficiency in cloud environments - Observability & Monitoring - Implement monitoring, logging, and alerting frameworks - Define and track database golden signals (latency, errors, throughput, saturation) - Build dashboards for health, performance, and capacity trends - Integrate telemetry into central observability platforms - Develop proactive alerting and anomaly detection - Data Replication & Migration - Design and manage replication strategies (logical, physical, CDC) - Implement and operate AWS DMS or equivalent tools - Enable near real-time data movement across systems - Troubleshoot replication lag and data consistency issues - Support large-scale database migrations (e.g., Oracle → PostgreSQL/Aurora) - Security & Access Control - Implement least privilege, role-based access controls - Enable Just-In-Time (JIT) access using PAM solutions (e.g., CyberArk) - Enforce secure access patterns and eliminate direct production DB access - Manage credentials using centralized secrets management - Ensure adherence to audit, compliance, and governance requirements - Support encryption standards (in transit and at rest) - Database & Data Access Engineering - Support data modeling, indexing, partitioning, and schema optimization - Demonstrate familiarity with modern database access technologies: - ORM frameworks (Hibernate, JPA, SQLAlchemy) - JDBC and connection management best practices - GraphQL and API-driven data access patterns - Design and promote Data Access Layer (DAL) architectures - Optimize data access patterns to improve performance and scalability - Developer Enablement & DevOps Integration - Manage database schema lifecycle using version-controlled tools (Liquibase/Flyway) - Enable automated deployments and zero-downtime database changes - Implement testing strategies for database changes - Partner with engineering teams to improve database usage patterns - Provide guidance on best practices, ORM usage, and performance tuning - Promote shift-left adoption of database design and reliability practices - Cloud Database Operations - Manage and support cloud database platforms, including: - AWS RDS / Aurora (PostgreSQL preferred) - DynamoDB - Oracle - SQL Server - MongoDB - MySQL - Other Responsibilities - Participate in a 24/7 on-call rotation Qualifications - Bachelor’s degree or equivalent experience - 7+ years in database engineering / DBA / DBRE roles - Strong experience in SQL, performance tuning, HA, backup, and recovery Preferred - AWS RDS / Aurora PostgreSQL experience - AWS DMS / CDC / replication experience - Observability tools (Datadog, Grafana, Prometheus, OpenTelemetry) - DevOps tools (Terraform, Ansible, Jenkins, GitHub Actions) - Python / shell scripting / REST APIs - JIT / PAM (CyberArk) experience - Data lake / warehouse / lakehouse exposure - Distributed systems / microservices experience - Linux/Unix expertise Target Compensation A competitive base salary range from $104,081 – $152,652. This position is eligible for an annual variable cash bonus, between 7.5 - 15%. Bonus amounts are based on individual performance. Final compensation within the range is influenced by many factors including role-specific skills, depth and experience level, industry background, relevant education and certifications. Candidates who reside in the following major metropolitan areas may be eligible for a premium on top of the posted range based on their specific zone: San Francisco, Seattle, Boston, New York City, Los Angeles and San Diego. 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 Company Values - 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

Role Description The Director of Sales Strategy & Analytics is responsible for leading the analytics, business insights, competitive intelligence, and Sales technology strategy that supports data-informed decision-making across the Sales organization. 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. Outcomes and Activities: - Lead the Sales analytics function, including a team of Sales Analysts supporting regional and enterprise Sales leadership. - Develop and execute the Sales Strategy & Analytics roadmap in alignment with organizational priorities, Sales objectives, and business needs. - Provide strategic insights and recommendations to improve Sales performance, productivity, profitability, and field execution. - Support strategic planning by identifying performance opportunities, risks, trends, and growth levers across the Sales organization. - Deliver executive-level insights and recommendations that support organizational priorities, Sales initiatives, and growth objectives. Performance Reporting and KPI Management: - Monitor regional performance, business trends, and key Sales metrics to evaluate progress against goals and priorities. - Oversee the development and management of Sales dashboards, reports, scorecards, and performance views. - Ensure Sales leaders have access to timely, accurate, and actionable reporting that supports business reviews, market reviews, coaching conversations, and performance decisions. - Partner with Sales Leadership to define, track, and refine key performance indicators that align to business objectives. - Use KPI reporting to identify performance gaps, highlight trends, and support leadership action. - Improve reporting consistency, usability, and adoption across the Sales organization. Profitability and Business Performance Analysis: - Lead analysis that supports improved profitability, resource allocation, market performance, and business outcomes. - Evaluate performance by region, market, dealer segment, product, initiative, or other relevant business dimensions. - Partner with Finance, Sales Leadership, and other stakeholders to connect Sales activity, market performance, and financial outcomes. - Provide insights that help leaders balance growth, productivity, profitability, and execution priorities. - Analyze performance patterns to support decisions in priority markets, underperforming markets, and high-growth markets. Competitive Intelligence and Market Analysis: - Lead competitive intelligence and market analysis efforts to identify opportunities, risks, trends, and business implications. - Partner closely with Product, Marketing, Sales Leadership, and other business partners to ensure market insights are incorporated into planning and decision-making. - Analyze competitive trends, market dynamics, dealer feedback, and business performance to support Sales strategies and field execution. - Translate competitive and market insights into practical recommendations for Sales leaders and cross-functional partners. - Support prioritization of sales plays, market actions, and performance improvement opportunities. Sales Technology Optimization and Enablement Platforms: - Serve as the business owner for Sales enablement technologies and platforms that support Sales execution, reporting, productivity, and field effectiveness. - Drive adoption, optimization, vendor management, and continuous improvement of Sales tools and platforms. - Partner with Sales Enablement, Sales Leadership, Product, Technology, Training & Development, and other stakeholders to ensure tools are aligned to Sales needs and business priorities. - Identify opportunities to improve Sales technology, reporting capabilities, data access, workflow efficiency, and user experience. - Use feedback, usage data, and performance insights to evaluate platform effectiveness and recommend improvements. - Support change management, communication, and readiness efforts related to new or enhanced Sales technologies. Cross-Functional Partnership and Strategic Planning: - Build strong partnerships across Sales, Sales Enablement, Product, Marketing, Finance, Training & Development, Technology, People, and other key stakeholders. - Serve as a trusted partner to Sales leaders by helping translate business needs into analytical insights, strategic recommendations, and execution support. - Support planning processes, business reviews, initiative prioritization, and performance management routines through data and insights. - Partner with cross-functional teams to align reporting, analytics, market intelligence, and technology priorities with broader business objectives. - Communicate complex information clearly and effectively to executive, regional, and field audiences. - Balance immediate business needs with long-term analytics capability, Sales effectiveness, and organizational growth. Organizational Health and Sales Strategy & Analytics Effectiveness: - Continuously evaluate and improve the Sales Strategy & Analytics function using the company’s Organizational Health framework. - Ensure the right team members are in the right roles and are performing at the expected level. - Assess team capacity, workload, and resource allocation to support Sales analytics, reporting, strategy, technology, and business insight priorities. - Ensure work is structured effectively to support Sales priorities, analytical support, strategic planning, technology ownership, and scalable reporting. - Confirm team members understand priorities, deliverables, role expectations, success measures, and execution standards. - Ensure the Sales Strategy & Analytics team has the skills, knowledge, and tools needed to support Sales leaders and business partners effectively. - Provide timely, direct, and consistent feedback; address performance gaps with clear action plans. - Use relevant metrics, stakeholder feedback, reporting adoption, platform usage, and business impact indicators to monitor team effectiveness and analytical value. - Support recognition practices that motivate performance, reinforce desired behaviors, and celebrate impact across the Sales Strategy & Analytics team. - Build trust, engagement, communication, collaboration, and alignment within the team and with key partners. - Identify opportunities to improve analytics tools, reporting processes, data governance, platform usage, technology support, and decision-making capabilities. Leadership and Talent Development: - Lead, develop, and coach a high-performing Sales Strategy & Analytics team. - Set clear expectations for team priorities, deliverables, analytical quality, execution standards, and performance outcomes. - Build team capability in analytics, business intelligence, profitability analysis, competitive intelligence, Sales technology, executive communication, and stakeholder partnership. - Create a culture of ownership, accountability, collaboration, curiosity, and continuous improvement. - Provide timely feedback and ensure team members are positioned to effectively support the Sales organization and cross-functional partners. Measurement and Continuous Improvement: - Establish success measures for Sales analytics, reporting, competitive intelligence, technology adoption, and strategic planning support. - Monitor the effectiveness, usage, and business value of reports, dashboards, insights, tools, and analytical support. - Identify opportunities to improve reporting quality, analytical depth, tool adoption, and decision-making support. - Partner with Sales Leadership and cross-functional teams to evaluate whether insights, tools, and recommendations are driving intended outcomes. - Continuously improve analytics capabilities, reporting processes, technology platforms, and business insight delivery to increase effectiveness, scalability, and measurable value. Qualifications - Bachelor’s degree or equivalent relevant experience. - 8 years of experience in Sales Strategy, Sales Analytics, Revenue Operations, Business Intelligence, Sales Operations, Sales Enablement, Finance, or related disciplines. - Experience leading analytics, reporting, business intelligence, strategy, or performance management functions. - Experience leading, developing, or coaching analytical talent. - Strong analytical, strategic thinking, problem-solving, and business acumen skills. - Demonstrated ability to translate complex data into clear, actionable business recommendations. - Strong understanding of Sales performance, KPI management, reporting, profitability analysis, and business planning. - Experience developing dashboards, scorecards, reporting routines, executive insights, or business review materials. - Ability to use data, reporting, and business insights to identify trends, evaluate performance, and drive action. - Strong communication, executive presentation, influence, and stakeholder management skills. - Experience leading cross-functional initiatives and influencing leaders across the organization. - Ability to manage multiple priorities in a fast-paced, evolving business environment. - Ability to build trust, strengthen partnerships, and influence decisions through data and insights. Requirements - Experience supporting large, distributed, or field-based Sales organizations. - Background in Sales Strategy, Revenue Operations, Sales Operations, Business Intelligence, Sales Enablement, or Sales Effectiveness functions. - Experience supporting complex B2B sales organizations. - Experience with competitive intelligence, market analysis, profitability analysis, or pricing-related business insights. - Familiarity with Sales enablement technologies, CRM platforms, reporting tools, business intelligence platforms, and data visualization tools. - Experience serving as a business owner or key stakeholder for Sales technology platforms, vendor relationships, or tool optimization. - Experience supporting organizational change, sales transformation, go-to-market execution, or strategic planning initiatives. - Strong cross-functional partnership with Sales, Product, Marketing, Finance, Training & Development, Technology, People, or other business partners. - Demonstrated success improving reporting adoption, analytical quality, Sales technology usage, decision-making, or business performance. 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.

• Develop and execute the Sales Readiness strategy in alignment with organizational priorities, Sales objectives, and business needs • Translate Sales priorities, go-to-market initiatives, product launches, and process changes into clear readiness plans and field execution support • Ensure Sales teams are prepared to execute strategic initiatives, new tools, updated processes, and Sales best practices • Establish scalable readiness programs that reinforce learning and support consistent execution across the Sales organization • Identify opportunities to improve seller productivity, field execution, and overall Sales performance • Lead a team responsible for ongoing Sales coaching, field readiness, and Sales development • Partner with Sales Leadership to identify capability gaps, execution challenges, and opportunities to improve Sales performance • Develop readiness programs that strengthen seller knowledge, skills, confidence, and execution discipline • Maintain content quality, consistency, and alignment with Sales priorities and company standards • Monitor program performance using data, feedback, participation, adoption, and business impact indicators.

• Design and develop software and improve existing code • Write unit-tests and validate your software against acceptance criteria • Apply team coding, documenting and testing standards • Conduct impact analysis to proactively identify impact of a change within an application • Participate in code reviews and communicate application changes • Document code and projects so others can easily understand, maintain and support • Debug the problems which arise in production and propose effective solutions • Read and write design documents • Learn the business process domain to better support the business • Contribute to team's sprint commitments and actively participate in our Agile practices • Contribute to continuous learning activities to improve design and code quality as well as to increase application domain knowledge • Guide and aid less experienced software engineers

Role Description We are seeking a highly motivated and experienced Leader of ML and AI Engineering within the AI team. The ideal candidate will have a strong technical background in decision science, machine learning, and generative AI with a proven track record in solving business problems and implementing large-scale automated solutions in partnership with the respective engineering teams. The leader will partner with business and engineering stakeholders to formulate the vision to achieve the company’s strategic goals and co-lead the roadmap to deliver innovative solutions for dealers, consumers, and team members. As a Senior Manager, MLE at Credit Acceptance, you will play a pivotal role in the success of this mission as you will lead the development of AI-powered solutions across different business areas. This involves understanding the business processes, identifying new opportunities to add value using ML/AI algorithms, and harnessing data sources to build state-of-the-art ML/AI solutions. This position will work from home; occasional planned travel to an assigned Southfield, Michigan office location may be required. However, this position is permitted to work at a Southfield, Michigan office location if requested by the team member. - Lead the vision and the strategic execution with a strong focus on continuous and long-term value creation across all participants of our flywheel. - Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans. - Drive execution and delivery of ML/AI solutions by managing priorities, deadlines, and deliverables, leveraging your technical expertise. - Design and deliver scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices, and nurture the culture of creating high-quality, well-tested systems to address critical product and business needs. - Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency. - Ensure the security, scalability, and architectural integrity of feature designs through reviews across teams. - Deliver hands-on solutions while mentoring other data professionals (including MLEs) within the organization. - Explore and apply advanced machine learning techniques, including large language models (LLMs), deep learning, and graph neural networks, to solve complex challenges across the organization. - Guide a team of MLEs across different areas: - Mentoring: Mentor team members on design principles, coding standards, and the adoption of AI productivity tools. - Recommendations: Personalize guidance across different surfaces using deep learning methods; personalize layouts with Bayesian contextual multi-armed bandits. - Growth: Foster long-term growth through data-driven causality and incrementality. - Gen-AI: Power existing applications with Gen AI models and engineering to improve downstream experience and decisions. - Lifecycle: Using ML models (such as XGBoost & Causal Meta-Learner-based model, etc.), proactively guide business teams across different areas. - Engineering: With engineering partners, build ML and Gen-AI platform and inference pipelines for different types of models. Qualifications - PhD in Computer Science, Stats, Economics, or a relevant technical field with at least 8+ years of relevant experience or MS with at least 10+ years of experience in machine learning and software engineering. - 8+ years of hands-on experience designing, building and deploying AI (ML, DL, Gen-AI) models, including Reinforcement Learning algorithms, Recommendation systems, Transformers, fine-tuned LLMs, Regressions, etc., with a solid understanding of mathematics, statistics, and engineering needed to build such infrastructure. - Hands-on expertise in scaling and maintaining production-grade ML services, with a strong focus on ML/LLM Operations (versioning, automation, observability, automated training and monitoring, etc.) and ability to balance ML model complexity with production requirements. - Passion for identifying new business opportunities and experience of using a test and learn approach to bring scalable and efficient solutions integrating AI algorithms, ML/LLM Ops, and s/w engineering. - Experience partnering with the engineering, product, business operations, legal and other teams while designing, building, and executing solutions. - Strong problem-solving skills with bias for action. Requirements - Experience in automotive industry, especially in building ML/AI systems while ensuring local and central regulations. - Experience in model interpretability and responsible AI practices. - Expertise in data science, advanced experimentation and visualization techniques. - Experience in designing and implementing pipelines using DAGs (e.g., Kubeflow, DVC, Ray). - Ability to construct batch and streaming microservices exposed as gRPC and/or GraphQL endpoints. - Experience with Databricks MLflow for ML lifecycle management and model versioning. - Hands-on experience with Databricks Model Serving for production ML deployments. - Proficiency with GenAI frameworks/tools and technologies such as Apache Airflow, Spark, Flink, Kafka/Kinesis, Snowflake, and Databricks. - Demonstrable experience in parameter-efficient fine-tuning, model quantization, and quantization-aware fine-tuning of LLM models. - Hands-on knowledge of Chain-of-Thoughts, Tree-of-Thoughts, Graph-of-Thoughts prompting strategies. 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. Company Description 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.

• 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