Connected Services Analytics

Stellantis•Auburn Hills, MI

About The Position

As part of the Data & Diagnostic insights initiative, the Connected Services Analytics & AI Enablement Lead accelerates adoption and value creation from connected vehicle data through advanced analytics, AI, and self-service capabilities. The role transforms connected services and digital product data into actionable insights, enabling business teams and engineering stakeholders to make data-driven decisions. It leads analytics solution development, defines reusable data assets, and promotes AI-powered approaches to improve customer understanding, product performance, and operational efficiency. The role develops scalable analytics solutions and data products using connected vehicle, feature usage, customer behavior, and operational data. It also enables AI and generative AI applications, collaborates with Data Scientists and AI experts to industrialize use cases, and designs scalable data processing workflows using Python, SQL, Spark, and cloud-based technologies. It supports data governance, standardization, documentation, monitoring, lifecycle management, and self-service analytics adoption.

Requirements

Bachelor’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
Minimum of 8 years of experience in Data Analytics, Data Science, AI enablement, or a similar role.
Ability to translate business challenges into scalable, reusable, data-driven analytics solutions that deliver business outcomes.
Good understanding of automotive domains, especially Connected Services, vehicle features, customer behavior analytics, or mobility services.
Experience working with large-scale data platforms and distributed processing environments.
Strong proficiency in Python, SQL, Spark/PySpark, and data visualization tools such as Power BI or equivalent.
Hands-on experience with Databricks or similar cloud data platforms.
Experience with AI and Generative AI concepts, including AI agents and intelligent workflows, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and machine learning lifecycle concepts.
Strong communication and collaboration skills with technical and non-technical stakeholders.

Nice To Haves

Master’s degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field.
Knowledge of data governance and data quality management best practices.

Responsibilities

Translate business needs and Connected Services challenges into scalable analytics solutions and data requirements.
Define and develop analytics use cases using connected vehicle, feature usage, customer behavior, 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.
Identify and develop opportunities to use Artificial Intelligence and Generative AI to enhance analytics capabilities.
Contribute to the design and deployment of AI-powered solutions, including AI assistants, analytics agents, and knowledge retrieval systems.
Define business rules, analytical logic, and data foundations for 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.
Design and implement scalable data processing workflows using Python, SQL, Spark, and cloud-based technologies.
Use 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 self-service analytics adoption by providing frameworks, methodologies, and guidance.