Senior Data Scientist focused on supply chain analytics at Emerson. Collaborating with cross-functional teams to enhance master data quality and drive operational improvements.
Responsibilities
Build strong partnerships with supply chain, procurement, manufacturing, and IT/data platform stakeholders to drive high-quality master data outcomes
Analyze how supply chain master data is created and consumed across upstream and downstream processes, identifying where defects originate
Perform data profiling and root‑cause analysis across key domains such as items, suppliers, BOM/routings, lead times, and locations
Apply statistical methods—including SPC, anomaly detection, and hypothesis testing—to define and maintain standards for S&OP Master Data and proactively detect data shifts
Use operations research techniques to test planning inputs and reveal weaknesses in system configurations, assumptions, and parameter settings
Develop and maintain scalable monitoring, data quality checks, and analytics solutions that connect directly to governance and remediation workflows
Communicate insights, impact, and recommended actions clearly to both technical and non‑technical audiences
Translate complex analytical findings into practical, implementable improvements in planning and execution processes
Requirements
Bachelor’s degree from an accredited institution
Strong proficiency in SQL and experience with Python or R for analysis and creating repeatable data quality logic
Demonstrated experience applying statistical methods to real-world, imperfect enterprise data
Hands-on expertise in operations research techniques such as optimization or simulation
Ability to work independently in ambiguous situations and drive end‑to‑end analytics workflows
Strong analytical judgment and a practical, solution-oriented mindset
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