Senior Data Analytics Engineer - Sandisk

ESSENTIAL DUTIES AND RESPONSIBILITIES:

• 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 .