Research Analyst (Technology)

Job Summary

We are seeking a highly capable Research Analyst (Technology) with expertise in AI compute ecosystems and enterprise storage technologies (ESSD/HDD). This role delivers data-driven insights to support strategic decision-making in investment, production, and R&D across semiconductor and storage sectors.

Responsibilities

• Analyze semiconductor, memory, and storage technologies from leading global manufacturers to generate actionable insights
• Evaluate AI model-driven compute demands by assessing GPU and accelerator utilization, memory bandwidth, and storage performance impacts
• Document and analyze manufacturing and qualification processes for enterprise SSDs (NVMe, PCIe Gen4/5), HDDs, and memory products to identify optimization opportunities
• Assess architectural trade-offs in ESSD/HDD, including controller design, NAND scaling, firmware optimization, endurance, latency, and power efficiency
• Monitor trends in AI infrastructure deployment and hyperscaler demand to evaluate effects on semiconductor, memory, and storage supply chains
• Review capacity allocation, utilization, and yield performance across wafer fabs and backend manufacturing for AI and storage workloads
• Identify operational bottlenecks and recommend improvements for yield enhancement, cost reduction, and technology transitions
• Develop insights on technology roadmaps such as NAND scaling, storage-class memory, and AI-driven storage acceleration to guide strategic planning
• Collaborate with cross-functional teams to support investment analysis, production planning, and R&D strategy formulation
• Prepare clear, well-structured technical reports, forecasts, and presentations for senior management and key stakeholders

Required competencies and certifications

• Bachelor’s or Master’s degree in Electrical Engineering, Semiconductor Engineering, Computer Engineering, Materials Science, or related discipline
• Demonstrated experience analyzing semiconductor manufacturing, memory, or storage technologies
• Strong understanding of AI compute ecosystems, including GPUs/accelerators, memory hierarchy, and storage performance requirements
• Solid knowledge of enterprise SSD and HDD technologies, including NAND flash, controllers, firmware, endurance management, and performance optimization
• Familiarity with process technologies and product roadmaps of Western Digital, Samsung, SK Hynix, and Micron
• Excellent analytical, problem-solving, and data interpretation skills
• Ability to translate complex technical findings into clear, actionable business and strategic recommendations

Other Information

• EA License Name & License Number: SMTP Consult Pte. Ltd. (23C1754)
• EA Personnel Name & Registration Number: Keith Wong (R24125987)

📩 Interested candidates, please submit your application for a confidential chat.