Connected Services Analytics & AI Enablement Lead

As part of the Data & Diagnostic insights initiative, we are looking for a Connected Services Analytics & AI Enablement Lead to accelerate the adoption and value creation from connected vehicle data through advanced analytics, AI, and self-service capabilities.

In this role, you will be responsible for transforming connected services & digital product data into actionable insights, enabling business teams and engineering stakeholders to make data-driven decisions. You will lead the development of analytics solutions, define reusable data assets, and promote AI-powered approaches to improve customer understanding, product performance, and operational efficiency.

Your key responsibilities will include:

Analytics & Data Product Enablement

• Translate business needs and Connected Services challenges into scalable analytics solutions and data requirements.
• Define and develop analytics use cases leveraging connected vehicle data, feature usage data, customer behavior data, and operational data.
• Design reusable analytics assets and data products to accelerate insight generation and decision-making.
• Ensure data consistency, quality, representativeness, and reliability through appropriate validation processes.
• Develop advanced analytics methodologies to uncover customer behaviors, product usage patterns, and feature performance insights.
• Build and maintain dashboards and visualization solutions to facilitate insight sharing and self-service analytics adoption.

AI & Intelligent Solution Enablement

• Identify and develop opportunities to leverage Artificial Intelligence and Generative AI to enhance analytics capabilities.
• Contribute to the design and deployment of AI-powered solutions such as AI assistants, analytics agents, and knowledge retrieval systems.
• Define business rules, analytical logic, and data foundations required to enable AI-driven applications.
• Prepare, structure, and curate datasets to support AI model development and intelligent workflows.
• Collaborate with Data Scientists and AI experts to industrialize machine learning and GenAI use cases.

Platform & Technical Leadership

• Design and implement scalable data processing workflows using Python, SQL, Spark, and cloud-based technologies.
• Leverage platforms such as Databricks to develop analytics pipelines and data processing solutions.
• Ensure best practices in data governance, documentation, monitoring, and lifecycle management.
• Promote standardization and reuse of analytics solutions across Connected Services domains.
• Support the adoption of self-service analytics tools by providing frameworks, methodologies, and guidance.