Dealer Audit - Data Analyst & AI Solutions

StellantisAuburn Hills, MI

About The Position

The role requires a creative and detail-oriented individual. In this role, you will develop and respond to requests for data analysis to present a coherent vision of business activities, assisting the Dealer Audit teams and key stakeholders in making data-driven decisions. The selected candidate will provide a blend of technical and functional expertise. AI Solutions: The role drives the identification, design, pilot, and scaling of AI and automation solutions across Dealer Audit. The role works to deliver measurable impact through workflow optimization, improved customer and employee experience, and digital process transformation. This role supports the broader organizational mission to accelerate digital transformation and scale AI adoption.

Requirements

  • Bachelor’s Degree in Business, Data Science, Statistics, Business Analytics, Management Information Systems, or a related field
  • A minimum of 5 years of experience as a Data Analyst, AI Analyst, or similar role
  • Strong knowledge of data visualization tools such as PowerBI, Tableau, Qlik, or similar tools
  • Familiarity with programming languages such as Python, R, SQL, NoSQL
  • Familiarity with platforms such as Visual Studio Code, Databricks, Snowflake, Palantir Foundry
  • Strong computer skills and highly proficient with Microsoft Office Suite (O365 / Online Collaboration Version)
  • AI literacy: understanding capabilities, limitations, risks, and responsible use
  • Flexible and adaptable to changing business environments and job responsibilities
  • Excellent written and verbal communication skills in English
  • Quantitative, analytical, and detail-oriented. Problem-solving skills
  • Strong project management skills; effective & efficient completing numerous tasks simultaneously
  • Knowledge of risk management, control objectives/activities, and automated/manual controls
  • Proficiency in data collection, warehousing, transformation, and analysis

Nice To Haves

  • Prior audit experience (financial, compliance, operational, or dealership/franchise)
  • Experience with automotive OEM dealership management systems
  • General understanding of the franchised dealership model
  • Experience with highly automated/digital processes; including but not limited to remote auditing techniques, claims processing, and optical recognition software
  • Advanced Degree in Business, Data Science, Statistics, Business Analytics, Management Information Systems, or a related field
  • 5+ years of (total) experience in the following areas: Automotive (Retail) – In-depth knowledge of dealership retail processes and procedures, with emphasis on fixed operations departments. Automotive (Technical) – In-depth knowledge of automotive technical information systems and repair/diagnostic procedures

Responsibilities

  • Analyze large and complex data sets from multiple sources to identify trends, patterns, and insights
  • Work with stakeholders to propose, identify, and develop analytics requirements
  • Build visualization or perform further analysis based on requirements identified
  • Know business data and provide recommendations for improving knowledge and data quality
  • Support audit teams in deepening their knowledge and utilization of data and AI within testing
  • Stay up-to-date with the latest advancements in AI and data analytics technologies
  • Identify high-value AI, Copilot, and other automation opportunities to embed into daily operations
  • Conduct process mapping and problem analysis to define requirements and value hypotheses
  • Translate business needs into clear user stories, requirements, and acceptance criteria
  • Partner with stakeholders to ensure feasibility and solution integration
  • Develop deployment playbooks, documentation, and training assets
  • Create reusable templates, prompt libraries, workflows, or automation components
  • Define KPIs and measure performance, productivity, and financial outcomes
  • Ensure compliance with Stellantis' Responsible AI and Data Governance frameworks
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