Lead data science initiatives to drive insights and operational efficiency within a manufacturing environment.
Responsibilities
Design and develop algorithms and models against large datasets to generate business insights.
Lead data science and analytics projects independently, from solution development to execution.
Build and maintain predictive and prescriptive models in production at enterprise scale.
Develop simulation, optimization, and what-if scenario planning tools to support decision making.
Communicate technical insights and recommendations to both technical and non-technical stakeholders.
Required Skills
7+ years of practical experience in data science, processing, and analytics.
Experience in manufacturing domains such as Smart Factory, Industry 4.0, or OEE.
Experience with predictive maintenance and parts management using AI/ML on robotic manufacturing lines.
Advanced knowledge of cloud big data, database technologies, and data pipeline development.
Experience building and running simulation and optimization tools.
Proven ability to lead projects and collaborate across cross-functional teams.
Expertise in sifting through data, identifying critical information, and developing hypotheses.
Advanced degree in Operations Research, Management Science, Industrial Engineering, Statistics, Mathematics, Economics, Computer Science, or a related field.
Preferred Skills
Experience with the Microsoft Azure stack, including Databricks and Power BI.