Senior Insights Architect - Analytics and AI

Job description

Job responsibilities

• Work closely with business stakeholders across Process, Design and Supplier Engineering functions to understand their analytics needs and translate them into scalable and performant technical solutions, including…
• Lead the design and development of complex analytics and data products that address Engineering challenges and opportunities, including predictive models, anomaly detection systems, and GenAI-powered tools, and drive…
• Evaluate, prototype, and recommend AI/ML approaches (supervised, unsupervised, and generative) to solve Engineering business problems.
• Manage the roadmap for analytics and data products, including AI/ML initiatives, aligning with Engineering strategic objectives, while effectively balancing competing requirements in a dynamic Engineering environment.
• Collaborate with data engineers, data scientists, ML engineers, and product engineers to ensure seamless integration and deployment of analytics and AI solutions.
• Ensure data quality, security, and governance across all analytics solutions, including responsible AI practices such as model explainability, bias detection, and compliance.
• Build strong relationships and influence stakeholders across the organization, particularly within Engineering functions, to gain buy-in and support for analytics and AI initiatives, and champion the adoption of AI…
• Stay up to date on the latest technologies and trends in data, analytics, and artificial intelligence, particularly as they relate to Engineering management.

Job requirements

• 10+ years of hands-on experience developing analytics solutions using Snowflake, Tableau, BOXI or similar tools using Engineering data.
• Hands-on experience with BOXI is a strong plus.
• Demonstrated experience building, collaborating in the deployment, and maintaining ML models and/or GenAI applications in a production environment.
• Experience collaborating with team working on large language models (LLMs) and prompt engineering, including integration of LLM APIs (OpenAI, Azure OpenAI, etc.) into data products.
• Functional understanding and data flows of Engineering systems and processes.
• Effectively communicate technical concepts — including AI model outputs and limitations — to non-technical audiences to foster understanding, influence, and build consensus across teams.
• A very good team player with demonstrated ability to manage and influence without direct authority.
• Strong understanding of data warehousing, data modeling, and visualization techniques.