Manager - Business Product Owner - Digital & Analytics (Distribution - Transportation)

Johnson & Johnson - Hopewell Township, NJ

Full-time - Manager

Hopewell Township, NJ

Chemical Manufacturing

About the position

The Manager - Business Product Owner - Digital & Analytics (Distribution - Transportation) at Johnson & Johnson will enhance distribution and transportation operations within the Innovative Medicines Global Deliver team. This role focuses on utilizing advanced modeling and simulation techniques to improve key performance indicators (KPIs) and ensure efficient supply chain operations. The ideal candidate will leverage data science expertise to drive operational improvements and support new product introductions while ensuring temperature control for sensitive products.

Responsibilities

• Define, track, and report on critical KPIs related to supply chain efficiency and effectiveness.
• Collaborate with cross-functional teams to ensure alignment on performance metrics.
• Develop insights to support root-cause analysis and action planning.
• Foster a data-driven culture in operations.
• Develop and implement predictive models to optimize distribution networks and transportation logistics.
• Conduct simulations to assess cost, capacity, and network efficiencies.
• Analyze historical data to identify trends and patterns that inform strategic decision-making.
• Support the introduction of new products by analyzing market trends and forecasting demand.
• Collaborate with product development teams to ensure logistical feasibility.
• Design models for monitoring temperature-sensitive products throughout the supply chain.
• Work with IT and engineering teams to implement real-time tracking systems.

Requirements

• Master's or Ph.D. in Data Science, Statistics, Computer Science, Engineering, or a related field.
• Minimum of 8 years of experience in data science or analytics roles, preferably within the pharmaceutical or logistics sectors.
• Proven track record of developing models that drive operational improvements.
• Proficiency in programming languages such as Python or R for data analysis and modeling.
• Strong experience with SQL for data manipulation and extraction.
• Familiarity with statistical analysis tools and methodologies (e.g., regression analysis, A/B testing).
• Excellent communication skills with the ability to present complex data insights to non-technical stakeholders.
• Strong problem-solving skills.