
Senior Product Manager
- Cincinnati, OH
- $71.00-76.00 per hour
- Contract
- Full-time
- Manage all technical aspects of a data driven product that captures and visualizes key business and technology KPIs and metrics through product lifecycle
- Work directly and indirectly with business stakeholders, vendors and third parties to ensure business needs are achieved
- Drive enablement of benefit value to the organization from data product offerings owned by this product space
- Create, maintain and communicate product and technology roadmaps, including near-term delivery, to engage stakeholders across the organization
- Identify, measure and improve key product metrics for a complex technology product to enhance the customer experience, and create a compelling, relevant product vision using metrics, customer insights, feedback, research and internal operational metrics
- Elicit, define and analyze medium to complex requirements in various formats ensuring they are testable, measurable and traceable
- Set criteria for minimum viable product to increase the speed/frequency with which enhancements and new capabilities are delivered
- Lead the appropriate teams to refine, prioritize and manage requirements using various tools (e.g., templates, team backlogs, requirements management or agile task management applications) for a data analytics product
- Lead requirement walk-throughs with key stakeholders using various methods (e.g., team demos, workshops, sprint planning and backlog refinement sessions)
- Solid understanding of the data industry, including trends, tools, best practices, and functionalities
- Proficiency with business analytics programs like Power BI
- Strong problem-solving skills and ability to think analytically
- Strong business acumen and understanding of how data can drive business decision
- Building a product roadmap for data-driven products
- Developing new data products in line with the product strategy
- Managing data science and engineering to enhance product experiences
- Managing the development of a data platform
- Background in Data Science, Data Engineering, Data Analysis, or Product Management