Identify, analyse, and resolve manufacturing process and quality-related issues through data-driven approaches.
Develop, implement, and maintain Fault Detection (FD), Predictive Analytics, and Run-to-Run (R2R) control models to improve process stability, yield, and equipment performance.
Lead and participate in continuous improvement initiatives focused on yield enhancement, cycle time reduction, productivity improvement, and manufacturing cost optimisation.
Perform exploratory data analysis (EDA) across multiple manufacturing data sources to uncover patterns, root causes, and improvement opportunities.
Design, develop, and deploy Advanced Process Control (APC) and Machine Learning models to address manufacturing quality and process challenges.
Collaborate with cross-functional teams including Process Engineering, Equipment Engineering, Quality, IT, and Operations to implement and sustain SPC, FDC, RMS, APC, and ML-based solutions.
Validate data quality, ensure data completeness, and monitor model performance to maintain solution effectiveness and reliability.
Develop model monitoring and retraining strategies to ensure long-term predictive accuracy and business value.
Document analytical methodologies, model assumptions, results, and lessons learned in knowledge management systems, ensuring documentation remains current and accessible.
Extract, transform, and analyse data using SQL, NoSQL, Python, Spark, and other analytics tools from manufacturing databases, historians, MES, equipment logs, and cloud platforms.
Communicate technical findings and recommendations effectively to stakeholders through dashboards, reports, and presentations.
Stay current with emerging technologies in Data Analytics, Artificial Intelligence (AI), Machine Learning (ML), Industrial IoT, and Smart Manufacturing to drive innovation and operational excellence.
REQUIRED:
At least 3 years of working experience in related field
Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Engineering, Applied Mathematics, or related disciplines.
Familiar with semiconductor manufacturing environment is an added advantage.
Strong problem-solving skills with the ability to translate complex manufacturing challenges into analytical and ML solutions.
Effective communication and stakeholder management skills with the ability to work across global and cross-functional teams.
PREFERRED:
Knowledge of manufacturing systems, including SPC, FDC, APC, RMS, MES, and semiconductor manufacturing processes is an advantage.
Familiarity with cloud-based analytics platforms, data pipelines, and big data technologies.
SKILLS:
Strong experience in Python, SQL, data analytics, and machine learning.
Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, XGBoost, or similar.
Basic knowledge of SQL
Good English skill, both written and oral
Good team work spirit
Able to develop and implement projects independently