Senior Supply Chain Expert Data Science & GenAI Enablement (Independent Candidate Only)
Posted 5 days ago by 1763183406
Negotiable
Outside
Remote
USA
Summary: The Senior Supply Chain Expert in Data Science & GenAI Enablement is a remote role focused on leading supply chain initiatives with a strong emphasis on data science and AI technologies. The position requires extensive experience in supply chain management, digital transformation, and collaboration with data science teams to develop AI-driven solutions. The expert will translate business priorities into actionable data science problem statements and drive the adoption of analytics across various supply chain functions. This role is ideal for a candidate with a deep understanding of supply chain processes and a passion for leveraging technology to enhance performance and sustainability.
Key Responsibilities:
- Act as the SME for planning, sourcing, manufacturing, logistics, and quality across JnJ MedTech / Innovative Medicine divisions.
- Convert business priorities (OTIF improvement, lead-time reduction, supplier reliability) into data science problem statements.
- Collaborate with Data Science, Data Engineering, and Product teams to ensure ML/AI solutions align with supply chain processes, constraints, and KPIs.
- Provide domain insights for key use cases such as demand sensing, ATP prediction, lead time forecasting, inventory optimization, supply risk sensing, and cost-to-serve analytics.
- Support scenario modeling and control tower intelligence by defining metrics, process linkages, and exception logic.
- Work with data scientists to define business logic, label data features, and validate ML outputs against real operational behavior.
- Review and challenge model assumptions (seasonality, MOQ, sourcing policies, safety stock logic, etc.).
- Support GenAI initiatives including automated audit preparation, supplier narratives, and root-cause summarization.
- Ensure AI/ML solutions are interpretable, explainable, and actionable.
- Measure and track the business impact of data science models (inventory turns, OTIF, cost-to-deliver, carbon footprint).
- Drive adoption of analytics, digital twins, dashboards, and AI-driven recommendations across planning, procurement, and logistics teams.
- Facilitate end-user enablement, training, and feedback loops.
Key Skills:
- 10+ years of end-to-end supply chain experience (MedTech, Pharma, or Consumer Health preferred).
- Strong knowledge of Plan Source Make Deliver Quality processes, data structures, and KPIs.
- Experience supporting or working with data science, analytics, or supply chain control tower initiatives.
- Functional experience with ERP and planning systems (SAP ECC/S4, JDE, OMP, Kinaxis, etc.).
- Ability to interpret analytical models (forecasting, regression, classification) and connect insights to operational decisions.
- Experience with Azure, Databricks, or Snowflake environments.
- Understanding of the AI/ML lifecycle (data prep, training, validation, deployment).
- Familiarity with digital twins, control towers, and GenAI applications.
- Strong communication and storytelling skills for senior leaders.
- Ability to thrive in a global, cross-functional, matrixed environment.
Salary (Rate): undetermined
City: undetermined
Country: USA
Working Arrangements: remote
IR35 Status: outside IR35
Seniority Level: undetermined
Industry: Other
Title: Senior Supply Chain Expert Data Science & GenAI Enablement
Location: Remote
Employment Type: Independent Candidate Only
About the Role
We are seeking a highly experienced Supply Chain leader with deep expertise across planning, operations, and digital transformation, combined with hands-on experience in Data Science, AI/ML, and Generative AI.
This role requires someone who understands end-to-end supply chain orchestration from strategic planning and supplier reliability to customer fulfillment and can translate that expertise into AI-powered, data-driven solutions that improve performance, resilience, and sustainability.
Key Responsibilities
< data-start="790" data-end="829">Supply Chain Domain Leadership</>Act as the SME for planning, sourcing, manufacturing, logistics, and quality across JnJ MedTech / Innovative Medicine divisions.
Convert business priorities (OTIF improvement, lead-time reduction, supplier reliability) into data science problem statements.
Collaborate with Data Science, Data Engineering, and Product teams to ensure ML/AI solutions align with supply chain processes, constraints, and KPIs.
Provide domain insights for key use cases such as demand sensing, ATP prediction, lead time forecasting, inventory optimization, supply risk sensing, and cost-to-serve analytics.
Support scenario modeling and control tower intelligence by defining metrics, process linkages, and exception logic.
Work with data scientists to define business logic, label data features, and validate ML outputs against real operational behavior.
Review and challenge model assumptions (seasonality, MOQ, sourcing policies, safety stock logic, etc.).
Support GenAI initiatives including automated audit preparation, supplier narratives, and root-cause summarization.
Ensure AI/ML solutions are interpretable, explainable, and actionable.
Measure and track the business impact of data science models (inventory turns, OTIF, cost-to-deliver, carbon footprint).
Drive adoption of analytics, digital twins, dashboards, and AI-driven recommendations across planning, procurement, and logistics teams.
Facilitate end-user enablement, training, and feedback loops.
Required Qualifications
10+ years of end-to-end supply chain experience (MedTech, Pharma, or Consumer Health preferred).
Strong knowledge of Plan Source Make Deliver Quality processes, data structures, and KPIs.
Experience supporting or working with data science, analytics, or supply chain control tower initiatives.
Functional experience with ERP and planning systems (SAP ECC/S4, JDE, OMP, Kinaxis, etc.).
Ability to interpret analytical models (forecasting, regression, classification) and connect insights to operational decisions.
Preferred Skills
Experience with Azure, Databricks, or Snowflake environments.
Understanding of the AI/ML lifecycle (data prep, training, validation, deployment).
Familiarity with digital twins, control towers, and GenAI applications.
Strong communication and storytelling skills for senior leaders.
Ability to thrive in a global, cross-functional, matrixed environment.