resume | Yuka Suzuki

Singapore

Worked in regulated healthcare and genomics contexts where technical outputs needed to support real-world interpretation and action.

Led requirements definition and rollout of an internal cloud-based sequencing analytics platform, materially improving turnaround time for internal users.
Defined product metrics and benchmarking approaches for a clinical oncology algorithm.
Automated design-verification test workflows, improving analysis speed and enabling more self-serve quality checks for non-technical users.
Supported scientists across multiple teams in adopting reusable data workflows and coding practices.

Delivered a cloud-scale machine learning platform to support an external drug discovery collaboration.
Defined use cases and product requirements for new analytical features on a genomics analytics platform.
Evaluated privacy-preserving approaches to inform data-sharing requirements.
Translated research-user needs into reproducible product demonstrations for population genomics contexts.

Captured and synthesised customer feature requests and pain points across APJ, helping inform roadmap and quality-improvement priorities across multiple genomics software products.
Identified and escalated an undocumented product limitation, coordinating stress-testing and supporting clearer documentation of the constraint.
Developed and delivered technical training workshops and product demonstrations for customers and partners across APJ.

Singapore

Worked across technical systems, scientific workflows, and early capability building in a fast-moving biotech startup environment.

Helped establish a new computational discovery capability by defining requirements for compute, tooling, and analytical workflows.
Built cloud-based computational infrastructure and translated research goals into practical execution plans across scientific and engineering teams.
Coordinated cross-functional work across multiple teams to keep analytical deliverables aligned with collaboration timelines and broader business priorities.
Helped shape the direction of an oncology analytics effort by clarifying use cases, analytical needs, and execution priorities for leadership discussions.
Automated a high throughput genetic-screening analysis workflow, materially reducing turnaround time and improving reproducibility.
Hired and supported a growing computational team during an early stage of capability buildout.

Singapore

Built a strong technical foundation in computational biology, genomics, and data-intensive research through PhD training.

Designed and launched an next-generation sequencing (NGS) cancer gene panel, defining the clinical use case and leading cross-disciplinary development with clinicians and biologists.
Co-authored 10 peer-reviewed publications in computational cancer genomics.
Organised annual data analytics workshops for 40+ postdoctoral fellows and clinician scientists across 3 years, translating complex computational methods for non-technical healthcare audiences.