Data Scientist - Troy, United States - Cynet Systems

Description

• 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 Magnas 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 is not to exceed 15%.
• 3+ 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).
• bility 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.
• dvanced 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.
• dvanced degree, applicable certification, or equivalent experience in Operations Research, Management Science, Industrial and Systems Engineering, Statistics, Mathematics, Economics, Computer Science or related field.