Job Description: - 3+ years of practical experience with data processing and analytics
- 1+ years in a data science role with experience in Manufacturing domain
- 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. Additional Language skills are an advantage (German, Spanish, Mandarin)
- 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%.