Description

Lead data science initiatives to drive insights and operational efficiency in a manufacturing environment.

Design and develop algorithms and models against large datasets to generate business insights. 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. Lead data science and analytics projects independently, from solution development to execution. Communicate technical insights and recommendations to both technical and non-technical stakeholders.

Responsibilities

• Lead end-to-end data science and analytics projects.
• Build and maintain enterprise-scale predictive models.
• Develop simulation and optimization tools for decision support.
• Translate complex data insights for technical and non-technical audiences.
• Collaborate across cross-functional teams to drive operational efficiency.

Required Skills

• 7+ years of practical experience in data science and analytics.
• Experience in manufacturing domains: Smart Factory, Industry 4.0, or OEE.
• Expertise in predictive maintenance and parts management using AI/ML on robotic lines.
• Advanced knowledge of cloud big data, database technologies, and data pipeline development.
• Proven ability to build and run simulation and optimization tools.
• Strong hypothesis development and critical data analysis skills.
• Advanced degree in Operations Research, Management Science, Industrial Engineering, Statistics, Mathematics, Economics, or Computer Science.

Preferred Skills

• Experience with the Microsoft Azure stack, including Databricks and Power BI.

Key Skills

Education

Any Graduate