Data Scientist

About the Opportunity

Our client is a leading semiconductor technology company seeking a motivated and analytical Data Scientist to support manufacturing, product engineering, quality, and yield improvement initiatives.

This role offers an excellent opportunity for recent graduates and early-career professionals to apply advanced analytics, machine learning, and artificial intelligence techniques to solve real-world semiconductor manufacturing challenges. The successful candidate will work closely with cross-functional engineering teams to transform large-scale manufacturing data into actionable business and engineering insights.

Key Responsibilities

• Perform advanced data analysis on manufacturing, testing, and production datasets to identify performance gaps, process variations, and yield-impacting factors.
• Develop predictive analytics and machine learning solutions to enhance manufacturing efficiency, product quality, and operational reliability.
• Translate complex engineering and manufacturing data into meaningful insights and recommendations for business and technical stakeholders.
• Design, build, and maintain automated reporting systems, dashboards, and performance monitoring tools to support data-driven decision-making.
• Partner with engineering, quality, and operations teams to investigate production issues and implement process improvement initiatives.
• Conduct statistical modelling, correlation studies, and root cause analysis to support quality enhancement and defect reduction efforts.
• Explore and implement AI-driven technologies to improve productivity, manufacturing intelligence, and operational performance.
• Optimize data workflows and analytics processes by leveraging cloud technologies and scalable computing resources.
• Present findings and recommendations to stakeholders through clear visualizations, reports, and presentations.
• Stay current with emerging trends in data science, artificial intelligence, and semiconductor manufacturing technologies.

Requirements

• Bachelor's degree in data science, Statistics, Computer Science, Electrical Engineering, Applied Mathematics, or a related discipline.
• Demonstrated knowledge of statistical modelling, predictive analytics, machine learning, and data mining methodologies.
• Hands-on experience with Python or R for data processing, analysis, and model development.
• Familiarity with database querying and management using SQL in large-scale data environments.
• Ability to work with complex datasets and transform data into actionable business or engineering insights.
• Strong analytical thinking, problem-solving ability, and attention to detail.
• Excellent communication and stakeholder management skills with the ability to explain technical concepts to diverse audiences.
• Self-motivated team player with a passion for innovation, continuous learning, and technology-driven problem solving.

Preferred Qualifications

• Exposure to semiconductor manufacturing, electronics production, or industrial engineering environments.
• Experience using data visualization platforms such as Tableau, Power BI, Looker, or similar tools.
• Understanding of Artificial Intelligence (AI), Generative AI, and Large Language Model (LLM) applications.
• Familiarity with cloud-based analytics platforms such as AWS, Azure, or Google Cloud Platform.
• Internship, research, or project experience involving manufacturing analytics, process optimization, or industrial data science.