Packaging Engineer (AI/ML)

Sandisk; George Town; On-site; MYR 90,000 - 150,000; Full time

Job summary

SanDisk in Penang, Malaysia, is seeking a Data Scientist with manufacturing data analytics expertise to join our global team. You will integrate data pipelines, analyze process data, and help drive Industry 4.0 initiatives across factory automation and IT.

You'll develop analytics and ML solutions using Python, R and SQL, support NPI transfers, optimize processes, conduct experiments, and collaborate with process, equipment and automation teams to deliver robust, scalable data-driven

Qualifications

• Bachelor’s or Master’s degree in Mechatronic Engineering, Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, Data Science, AI, ML or related field.
• Minimum 3 years relevant working experience as data scientist or in an engineering field.

Responsibilities

• Integrate assembly/test data pipeline, analyze and transform process data.
• Develop new process for NPI, transfer to HVM without major quality issues.
• Analyze and optimize existing manufacturing processes to enhance efficiency and product quality.
• Develop and implement process improvement initiatives using Six Sigma and Lean.
• Design and conduct experiments to troubleshoot process issues and validate improvements.
• Develop and maintain factory automation applications with modern frontend tools.
• Develop and optimize Oracle SQL and Microsoft SQL Server queries for data access and reporting.
• Integrate factory systems and manufacturing equipment via web services, API calls, or SECS/GEM communication protocols.
• Collaborate closely with process, equipment, factory automation and IT teams to deliver robust and efficient automation, machine learning and AI solutions.

Skills

Statistics JMP

Machine Learning

Python

R

SQL

Education

Bachelor’s or Master’s degree in a related technical field

Tools

JMP software

SQL Server

Job description

Sandisk understands how people and businesses consume data and we relentlessly innovate to deliver solutions that enable today’s needs and tomorrow’s next big ideas. With a rich history of groundbreaking innovations in Flash and advanced memory technologies, our solutions have become the beating heart of the digital world we’re living in and that we have the power to shape.

Sandisk meets people and businesses at the intersection of their aspirations and the moment, enabling them to keep moving and pushing possibility forward. We do this through the balance of our powerhouse manufacturing capabilities and our industry-leading portfolio of products that are recognized globally for innovation, performance and quality.

Sandisk has two facilities recognized by the World Economic Forum as part of the Global Lighthouse Network for advanced 4IR innovations. These facilities were also recognized as Sustainability Lighthouses for breakthroughs in efficient operations. With our global reach, we ensure the global supply chain has access to the Flash memory it needs to keep our world moving forward.

Description

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Integrate assembly/test data pipeline, analyze and transform process data.
• Develop new process for NPI, transfer to HVM without major quality issues.
• Analyze and optimize existing manufacturing processes to enhance efficiency and product quality.
• Develop and implement process improvement initiatives using methodologies such as Six Sigma and Lean.
• Design and conduct experiments to troubleshoot process issues and validate improvements.
• Develop and maintain factory automation applications with modern frontend tools.
• Develop and optimize Oracle SQL and Microsoft SQL Server queries for data access and reporting.
• Integrate factory systems and manufacturing equipment via web services, API calls, or SECS/GEM communication protocols.
• Collaborate closely with process, equipment, factory automation and IT teams to deliver robust and efficient automation, machine learning and AI solutions.

Required

• Bachelor’s or Master’s degree in Mechatronic Engineering, Computer Engineering, Computer Science, Software Engineering, Electrical Engineering, Data Science, Artificial Intelligence, Machine Learning or a related technical field.
• Min 3 years relevant working experience, as data scientist or engineering field.

Preferred

• Data Scientist with manufacturing/engineering knowledge.

Skills

• Proficiency in statistical data analysis using JMP software. Knowledge of statistical techniques in data science (regression, properties of distribution).
• Knowledge in machine learning techniques (neural network, machine learning). Knowledge in programming language (python, R) and database (SQL) to perform data mining and analysis.
• Strong analytic skills and problem-solving skills.
• Experience or academic projects related to manufacturing automation, MES integration, or factory data systems.
• Exposure to Industry 4.0 technologies, real-time dashboards, or digital transformation initiatives in manufacturing. Passionate about technology and continuous improvement in a factory environment.
• Strong communication and teamwork skills. Self-motivated, organized, and able to manage multiple tasks in a dynamic environment.

Additional Information

Sandisk thrives on the power and potential of diversity. As a global company, we believe the most effective way to embrace the diversity of our customers and communities is to mirror it from within. We believe the fusion of various perspectives results in the best outcomes for our employees, our company, our customers, and the world around us. We are committed to an inclusive environment where every individual can thrive through a sense of belonging, respect and contribution.

Sandisk is committed to offering opportunities to applicants with disabilities and ensuring all candidates can successfully navigate our careers website and our hiring process. Please contact us at [e-mail] to advise us of your accommodation request. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.