Job Description:
- 7+ years of practical experience with data science / processing and analytics
- Experience in Manufacturing domain: smart manufacturing / smart factory / Industry 4.0 / OEE (overall equipment efficiency)
- Project Lead experience: ability to connect with different teams in an organization and lead to success
- Ability to help the different teams to achieve success
- Predictive maintenance & Parts Management, using AI / ML (machine learning) on the manufacturing line that contains Robots
- Ability to sift through data, identify critical information, analyze, develop hypothesis and make recommendations to broader audience required
- Experience developing and running simulation, optimization, and what-if scenario planning tools to support decision making
- Experience building and maintaining predictive and/or prescriptive models in production at enterprise scale
- Excellent written and verbal communication skills in English language, including ability to develop and deliver presentation.
- Advance Knowledge and engineering skills in (Cloud) big data & database technologies, data management & data pipeline development
- Experience with Microsoft Azure stack (Azure Data Warehouse, Databricks, Azure Analysis Services, Power BI) is an advantage
- Advanced degree, applicable certification, or equivalent experience in Operations Research, Management Science, Industrial and Systems Engineering, Statistics, Mathematics, Economics, Computer Science or related field
Major Responsibilities
· Design and develop algorithms and models to use against large datasets to create business insights. Incorporate business knowledge into solution approach by trustful collaboration with internal customers and cross-functional teams
· Lead Data Science & Analytics projects & initiatives and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Prepare reports, updates and presentations related to progress made on a project or solution
· Effectively communicate insights, recommendations and its impact to both technical and non-technical leaders and business partners
· Participate in establishing and continuously improving Magna’s data science practice by developing replicable solutions (e.g. codified data products, recipes, project documentation, process flowcharts)
· Seek further knowledge on key developments within data science, technical skill sets, and additional data sources
· Regular travel not to exceed 15%.