Our vision is to transform how the world uses information to enrich life for all.
Join an inclusive team passionate about one thing: using their expertise in the relentless pursuit of innovation for customers and partners. The solutions we build help make everything from virtual reality experiences to breakthroughs in neural networks possible. We do it all while committing to integrity, sustainability, and giving back to our communities. Because doing so can fuel the very innovation we are pursuing.
We are looking for an accomplished Manager, Data Science to lead the next evolution of our TD NAND data science and analytics capabilities in Singapore .
This is a high-impact leadership role at the intersection of semiconductor manufacturing, data science, advanced analytics, and engineering . You will lead teams that apply statistical methods, machine learning, data engineering, and advanced analytics to solve complex manufacturing challenges and improve process capability, device yield, and operational performance .
Working closely with Process Integration, Process Engineering, Inline/Metrology/RDA, Yield, and other cross-functional engineering teams , you will transform large and complex datasets into actionable engineering insights.
You will also play a hands-on role in shaping analytical approaches, developing prototypes, enabling rapid ad-hoc analysis, identifying sources of variation (SOV), and building scalable algorithms and automated data solutions using inline, parametric, probe, sensor, and equipment data .
Because of the highly technical nature of this role, strong semiconductor manufacturing knowledge and experience are essential .
What You’ll Do
Lead & Develop High-Performing Teams
Lead and develop global engineering and analytics teams across multiple levels. Recruit, mentor, and grow analysts, engineers, and contractors while fostering a culture of technical excellence, innovation, collaboration, and continuous improvement.
Drive Yield & Process Optimization
Partner with semiconductor manufacturing and engineering teams to analyze inline, parametric, and probe data, identify key yield detractors, troubleshoot manufacturing issues, and drive continuous improvement.
Build Data Pipelines & Automation
Extract, cleanse, integrate, and analyze large datasets from SQL databases, sensor networks, fabrication equipment, and other manufacturing data sources.
Advance Analytics & Machine Learning
Apply statistical modeling, machine learning, and data science techniques to identify patterns, understand sources of variation, troubleshoot yield issues, and support defect reduction strategies.
Enable Engineering Experimentation
Partner with Process and Integration Engineers to design and analyze Design of Experiments (DOE) , improving process capability, margins, and manufacturing performance.
Turn Data into Actionable Insights
Develop automated reports, analytical tools, prototypes, and dashboards using technologies such as Dash, Plotly, and Streamlit , making complex engineering insights accessible to key stakeholders.
Lead Cross-Functional Execution
Manage a multi-stream analytics and data engineering portfolio while partnering with Yield, LPD, Cost, IET, Planning, and other engineering leaders to align priorities, dependencies, risks, and delivery.
What You Bring
Minimum Qualifications & Experience
Master’s degree in Computer Science, Electronics Engineering, or a related technical discipline .
12+ years of overall professional experience , including at least 2–3 years leading global Analytics and/or Data Science teams .
Strong hands-on experience within the semiconductor industry .
Solid understanding of semiconductor fabrication processes, manufacturing equipment, and device physics .
Essential Technical Expertise
Programming & Data Engineering: 8+ years of experience working with Python and strong proficiency in SQL for data extraction, transformation, and analysis.
Cloud & Data Platforms: Experience with GCP and Snowflake…