Data Scientist
Core
Design, develop, and deploy advanced analytics and AI-driven solutions to analyze large-scale engineering, PLM, and BOM datasets to enable early identification of product, part, and lifecycle risks.
Role type
Senior Data Scientist (Engineering Analytics)
Builds
Scalable analytics solutions, interactive dashboards, and AI models for product readiness and risk monitoring
Domain
Semiconductor manufacturing / Materials engineering / Product Lifecycle Management
Deliverable
production ML models | dashboards & analysis
Required skills
Machine learning, statistical modeling, Python, SQL, Databricks, Apache Spark, Tableau, enterprise data integration, feature engineering, model deployment and monitoring
Preferred skills
Low-code analytics platforms (Mendix), experience with Teamcenter and SAP PLM/ERP systems
Technologies
Databricks, Apache Spark, Tableau, Mendix, Teamcenter, SAP
Responsibilities
Develop and implement advanced statistical, machine learning, and AI models for BOM, part, supplier, and lifecycle risk analytics; Analyze and integrate data from enterprise systems including Teamcenter PLM and SAP; Design, build, and deploy scalable analytics solutions using Databricks and Spark-based platforms; Lead end-to-end data science projects, including data discovery, feature engineering, model development, deployment, and monitoring; Build and maintain dashboards and analytics applications using Tableau and low-code platforms such as Mendix; Mentor junior data scientists and establish best practices for modeling, validation, and analytics governance
Seniority
Senior, hands-on IC with mentorship responsibilities
