What are the responsibilities and job description for the Technical Product Manager III position at IntePros?
IntePros is seeking a Technical Product Manager to join our premier client. In this role, you will lead the measurement and operational data/analytics setup for a Fleet and Packaging media channel and expansion scoping. The ideal candidate thrives in a fast-paced environment, enjoys solving ambiguous problems, and excels at cross-functional collaboration.
Key Responsibilities
Key Responsibilities
- Define the strategic vision and roadmap for measurement models and operational analytics tools for Fleet and Packaging media channels.
- Translate business needs into logical measurement designs that balance data processing effort, operational excellence, and customer insights.
- Partner with product, operations, engineering, and science teams to build best-in-class measurement models and analytics capabilities.
- Develop analytics dashboards and monitoring tools to track operational efficiency and program impact.
- Scope product expansion to other markets based on insights from the current setup.
- Lead all stages of the product lifecycle, from concept to delivery.
- Communicate ideas effectively to diverse audiences, both verbally and in writing.
- 5 years of product or program management, product marketing, business development, or technology experience.
- Bachelor’s degree.
- Experience with feature delivery and tradeoffs of a product.
- Experience owning and driving roadmap strategy and definition.
- Experience with end-to-end product delivery.
- Experience contributing to engineering discussions around technology decisions and strategy related to a product.
- Experience managing technical products or online services.
- Experience representing and advocating for a variety of critical customers and stakeholders during executive-level prioritization and planning.
- Experience using analytical tools such as Tableau and QuickSight.
- Experience building and driving adoption of new tools.
- Familiarity with concepts such as system architecture, optimization, system dynamics, system analysis, statistical analysis, reliability analysis, and decision-making.
- Experience with machine learning to support model automation.