Sr. Product Manager

Job Location: Dallas, TX

Open to Dallas or Hershey, PA

Role Overview: The Sr. Product Manager role is responsible for leading and managing data-centric projects that drive operational efficiencies and strategic insights. This role involves overseeing the development and implementation of data management frameworks, ensuring data quality and integrity, and collaborating with cross-functional teams to support supply chain optimization and decision-making processes. The individual will work closely with stakeholders to align data initiatives with business objectives, drive data-driven decision-making, and ensure the successful execution of data programs that enhance supply chain performance.

Responsibilities:

1. Develops and communicates product vision, strategy, and roadmap in alignment with overall supply chain, business and technical goals
2. Continuously collects and analyzes data to identify opportunities for product improvement and market optimization
3. Enforces agile methodologies throughout projects, actively participates in sprint planning, manages the backlog, and makes key prioritization decisions
4. Business fundamentals including financial management, metrics reporting, business process management, customer centricity, business analysis and problem solving
5. Data Program Oversight: Manage data programs and projects from initiation through to delivery, ensuring alignment with supply chain objectives and business goals. Oversee project timelines, budgets, and resources to achieve successful outcomes.
6. Data Quality Management: Develop and enforce data governance policies, procedures, and tools to maintain high data quality and integrity. Conduct regular audits and assessments to identify and address data quality issues.
7. Stakeholder Collaboration: Collaborate with supply chain, IT, and business units to understand data needs and requirements. Facilitate communication between teams to ensure data solutions are effectively integrated and meet user needs.
8. Strategic Insights and Reporting: Analyze and interpret data to provide actionable insights and recommendations for supply chain optimization. Develop and deliver reports, dashboards, advanced analytics, and AI solutions to deliver value cases for Supply Chain and to support strategic decision-making.
9. Process Improvement: Identify opportunities to improve supply chain outcomes through optimization using advanced data and analytics techniques and AI. Implement best practices and innovative solutions to enhance data collection, analysis, and reporting capabilities to deliver value against Supply Chain value use cases.

Qualifications:

• Product Management: Deep understanding of product technology and architecture; Strong project management and problem-solving abilities
• Market Research & Journey Mapping: Strong analytical skills for market research and data-driven decision-making; Ability to write clear user stories with well-defined acceptance criteria and technical documentation
• Strategic Planning: Adept ability to align product strategy with long-term business goals
• Data Management Expertise: Deep understanding of data management principles, practices, and technologies. Ability to design and implement robust data governance frameworks to ensure data accuracy and consistency.
• Technical Proficiency: Proficiency in data management and analytics tools such as SQL, Python, and data visualization software. Familiarity with supply chain management systems and processes is advantageous.

Experience & Education:

• Education: Strong preference for MBAs with undergrad in a technical field (Computer Science, Engineering, Information Systems, Analytics, Mathematics, or a related field)
• Experience: Minimum of 7 years of experience in data management, data analysis, or related roles, with at least 3 years in a product management or leadership capacity. Experience within the supply chain or consumer packaged goods industry is highly preferred.
• Experience managing the development of applications that leverage data science techniques and machine learning.

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