Job Summary
As a Data Scientist, you will design, develop, and deploy advanced analytics and AI-driven solutions to analyze large-scale engineering, PLM, and BOM datasets. Your work will enable early identification of product, part, and lifecycle risks and support data-driven decision-making before and after product release.
This role partners closely with Released Product Engineering, Design Engineering, PLM, Manufacturing, Safety, Quality, and Reliability teams. You will translate complex data from enterprise systems such as Teamcenter and SAP into actionable insights, scalable analytics solutions, and interactive dashboards.
In addition to hands-on technical contributions, you will lead analytics initiatives, mentor junior team members, and help shape how data science influences engineering, release, and risk decisions at scale.
Key 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, SAP (E), and other engineering data sources
- 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
- Enable data-driven decision-making for product readiness, new part release monitoring, and option optimization
- Collaborate with cross-functional engineering, manufacturing, and IT teams to translate complex datasets into clear, actionable insights
- Mentor junior data scientists and establish best practices for modeling, validation, and analytics governance
- Stay current with emerging data science, AI, and enterprise analytics trends
Required Qualifications
- 6+ years of full-time experience as a Data Scientist or in an equivalent analytics role
- Postgraduate degree in Data Science, Computer Science, Statistics, Engineering, or a related field
- Strong foundation in machine learning, statistical modeling, and data analysis techniques
- Proficiency in Python; strong SQL skills preferred
- Experience working with large, structured enterprise datasets
- Hands-on experience with Databricks, Apache Spark, or similar big data platforms
- Experience integrating and analyzing data from Teamcenter, SAP, or other PLM / ERP systems
- Strong experience building dashboards and visual analytics using Tableau
- Exposure to low-code or app-based analytics platforms such as Mendix is a plus
- Strong communication skills and ability to collaborate with cross-functional teams
Why Join This Role
- Work on high-impact engineering, PLM, and product analytics problems
- Influence early product, release, and risk decisions using data and AI
- Collaborate with senior engineering, manufacturing, and leadership stakeholders
- Opportunity to scale analytics solutions from pilot initiatives to enterprise-wide adoption
- Be part of a team shaping the future of data-driven engineering and release decisions