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Tier-1 employer, remote posting, and a mid-level generalist Data Scientist title increase applicant competition.
Requires PLM, BOM, and manufacturing domain knowledge making cross-industry transfer limited.
Explicit 6+ years, postgraduate degree, and specific Databricks/Spark/PLM tool requirements enforce strict filters.
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Design, develop, and deploy AI-driven advanced analytics solutions for large-scale engineering, PLM, and BOM datasets to identify product, part, and lifecycle risks.
Lead end-to-end data science projects including model development, deployment, and dashboard creation to support decision-making in product readiness and risk management.
Collaborate cross-functionally with engineering, manufacturing, and leadership teams and mentor junior data scientists to scale analytics solutions enterprise-wide.
Minimum 6 years of experience as a Data Scientist or equivalent analytics role.
Postgraduate degree in Data Science, Computer Science, Statistics, Engineering, or related field.
Strong proficiency in Python and strong SQL skills preferred; experience with Databricks, Apache Spark, and working with enterprise datasets from Teamcenter, SAP or similar PLM/ERP systems.
Experience in building dashboards with Tableau; exposure to low-code analytics platforms (e.g., Mendix) is a plus.
Experienced in handling structured enterprise data for engineering and manufacturing domains, particularly with PLM and ERP systems.
Capable of leading analytics initiatives with a focus on scalable AI and machine learning solutions to influence product release and risk decisions.
Able to communicate effectively with cross-functional and senior leadership stakeholders to operationalize data-driven insights at scale.