Senior Consumer Insight Analyst

Responsibilities

• Lead analysis for a scenario-based market modeling tool addressing key business questions across pricing, marketing, planning, and forecasting.
• Serve as a consultant, trainer, subject matter expert, and storyteller, translating model outputs into clear recommendations.
• Drive platform innovation and enhancements to improve impact and usability.
• Manage the strategy supplier partner developing and enhancing the market model.
• Represent the voice of the customer across cross-functional teams to reflect customer priorities and needs.
• Deliver consumer and market insights to stakeholders across Marketing, Planning, Engineering, Program Management, Vehicle Experience, and Design.
• Build expertise in analytical tools, data sources, and automotive market trends.
• Analyze internal and external data to identify insights and recommend actions.
• Create clear, compelling presentations that inform strategic and leadership decisions.
• Partner across GM Global Customer Research to identify knowledge gaps and shape additional research.
• Build understanding of the global vehicle development process and where consumer input is most critical.
• Explore new approaches, including AI and emerging technologies, to deliver trusted, high-quality insights.

• Bachelor’s degree in Business, Market Research, Analytics, Behavioral Science, or related.
• 5+ years of experience in consumer research, insights, planning, and/or marketing; internship and co‑op experience does not count.
• Critical thinking and analytical skills, including the ability to turn complex data into concise, actionable insights.
• Ability to solve complex, ambiguous problems using data‑driven approaches.
• Proven success working in cross‑functional, team‑based environments.
• Excellent communication skills, including presenting to senior leadership.
• Strong project management and organizational skills, with the ability to manage multiple priorities and deadlines.
• Familiarity with statistical methods, including factor, cluster, and latent class analysis, and experience with conjoint and advanced techniques such as TURF, elasticity modeling, Max Diff, and segmentation.
• Proficiency in Microsoft Word, PowerPoint, and Excel.
• Commitment to accurate, relevant, and high-quality analysis.