Data & AI Product Leader: Strategy, Adoption & Impact

Penske Logistics; Beachwood (OH); Remote; USD 110,000 - 160,000; Full time

Job summary

Penske Logistics is seeking a Product Manager for Data and AI to own the roadmap from validated opportunities through production and continuous improvement. You will partner with PQS, Operations, and technical teams to translate operational needs into measurable product outcomes.

Lead adoption and value realization, working with Data Engineering, Data Science, Cloud Engineering, Security, and IT to scale solutions and demonstrate impact.

Qualifications

• Bachelor’s degree in a related field required.
• Master’s degree preferred.
• Minimum of 4 years of product management, technology, analytics, data, or related experience.
• Minimum of 1 year of experience managing Data, AI, analytics, or software products preferred.
• Advanced product management skills and strong business/analytical capabilities required.
• Intermediate technical & data fluency is expected.

Responsibilities

• Owns product strategy, roadmap, requirements, and lifecycle for assigned Data and AI products.
• Serve as primary business liaison with PQS, Operations and stakeholders to define problems and outcomes.
• Collaborate with Data Engineering, Data Science, Cloud Engineering, Security, IT to scale prototypes to production.
• Drive adoption, training, change management, and measure product impact.
• Define and realize business value, including time and cost savings and revenue impact.
• Apply PM standards and operating model to support a product-oriented organization.

Skills

Product management

Data & AI product

Stakeholder management

Analytical skills

Education

Bachelor’s degree in Business, CS, Engineering, Operations, Supply Chain, Logistics, IS

Master’s degree

Job description

Penske Logistics is seeking a Product Manager for Data and AI to own the roadmap from validated opportunities through production and continuous improvement. You will partner with PQS, Operations, and technical teams to translate operational needs into measurable product outcomes.

Lead adoption and value realization, working with Data Engineering, Data Science, Cloud Engineering, Security, and IT to scale solutions and demonstrate impact.