Overview
Remote
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 12 Month(s)
Skills
Science
Supply Chain Management
Strategic Planning
Logistics
Machine Learning (ML)
Inventory Optimization
Generative Artificial Intelligence (AI)
Data Science
Artificial Intelligence
Job Details
About the Role
We are looking for an exceptional supply chain leader with extreme depth in planning, operations, and digital transformation, combined with proven experience in data science, AI/ML, and Generative AI.
This role demands an individual who understands the science of supply chain orchestration from strategic planning and supplier reliability to customer promise and fulfillment and can convert that knowledge into AI-powered, data-driven solutions that transform performance, resilience, and sustainability.
Key Responsibilities
Supply Chain Domain Leadership
- Serve as the functional SME for planning, sourcing, manufacturing, logistics, and quality across JnJ MedTech / Innovative Medicine divisions.
- Translate business priorities (e.g., improved OTIF, reduced lead time, supplier reliability) into data science problem statements.
- Partner with Data Science, Data Engineering, and Product teams to ensure algorithms align with supply chain processes, constraints, and KPIs.
- Provide domain insights for use cases like demand sensing, ATP prediction, lead time forecasting, supply risk sensing, inventory optimization, and cost-to-serve analytics.
- Enable scenario modeling and control tower intelligence by defining process linkages, performance metrics, and exception logic.
Data Science Collaboration
- Work closely with data scientists to define business logic, label data features, and validate ML outputs against operational truth.
- Review and challenge model assumptions using supply chain expertise e.g., seasonality, MOQ constraints, safety stock rules, or sourcing policies.
- Support GenAI initiatives that automate audit preparation, supplier performance narratives, or root cause summarization.
- Ensure all AI solutions are interpretable, explainable, and actionable for business users.
Value Realization & Change Management
- Quantify and track the impact of data science models on supply chain KPIs (inventory turns, OTIF, cost-to-deliver, carbon footprint).
- Partner with planners, procurement leads, and logistics teams to embed analytics in daily decision workflows.
- Facilitate end-user training and adoption of dashboards, digital twins, and AI-driven recommendations.
- Promote continuous improvement through feedback loops between business and data teams.
Required Qualifications
- 10+ years of end-to-end supply chain experience, preferably in MedTech, Pharmaceuticals, or Consumer Health.
- Strong understanding of Plan Source Make Deliver Quality processes, data structures, and KPIs.
- Experience working with or supporting data science, analytics, or control tower initiatives.
- Functional knowledge of ERP and Planning Systems (SAP ECC/S4, JDE, OMP, Kinaxis, etc.).
- Ability to interpret analytical models (forecasting, classification, regression) and connect them to operational use cases.
Preferred Skills
- Experience collaborating with data engineering teams using Azure, Databricks, or Snowflake environments.
- Understanding of AI/ML lifecycle (data preparation, model training, validation, deployment).
- Familiarity with control tower ecosystems, GenAI applications, or digital twins.
- Excellent storytelling skills able to simplify analytical outputs for senior stakeholders.
- Proven ability to work in a matrixed, cross-sector, and global environment.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.