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.