Senior Full Stack Engineer, Data Science

Fred Hutchinson Cancer Center•Seattle, WA

22h•Hybrid

About The Position

Fred Hutchinson Cancer Center is an independent, nonprofit organization providing adult cancer treatment and groundbreaking research focused on cancer and infectious diseases. Based in Seattle, Fred Hutch is the only National Cancer Institute-designated cancer center in Washington. With a track record of global leadership in bone marrow transplantation, HIV/AIDS prevention, immunotherapy and COVID-19 vaccines, Fred Hutch has earned a reputation as one of the world’s leading cancer, infectious disease and biomedical research centers. Fred Hutch operates eight clinical care sites that provide medical oncology, infusion, radiation, proton therapy and related services, and network affiliations with hospitals in five states. Together, our fully integrated research and clinical care teams seek to discover new cures to the world’s deadliest diseases and make life beyond cancer a reality. At Fred Hutch we value collaboration, compassion, determination, excellence, innovation, integrity and respect. Our mission is directly tied to the humanity, dignity and inherent value of each employee, patient, community member and supporter. Our commitment to learning across our differences and similarities make us stronger. We seek employees who bring different and innovative ways of seeing the world and solving problems. The Human Biology Division cultivates interdisciplinary research to advance understanding of human biology and the complex problems of neoplasia and other human diseases. The division is structured to foster laboratory-based and computational research at the interface of basic, clinical and population sciences. The Holland Lab is seeking a Senior Full Stack Engineer, Data Science to drive the Oncoscape platform, a production-grade system for cancer research. This hybrid role combines full-stack software engineering with hands-on data science, with control over both the product and the analysis of large-scale clinical and genomic datasets. You will build intuitive user interfaces, design scalable backend systems, and develop analytical methods for high-dimensional data—all while collaborating closely with researchers and clinicians to turn complex scientific questions into robust software and actionable insights. In this role, you will deliver high-impact software and directly contribute to computational oncology research, shaping the platform and the discoveries it enables. This role will have the opportunity to work partially at our campus and remotely.

Requirements

BS in Computer Science, Engineering or related field, or equivalent combination of education and professional experience.
Minimum of 6 years directly related experience.
Expertise with modern programming paradigms in a language such as Java, C#, Python or JavaScript.
Other department-determined skills or experience may be required

Nice To Haves

3+ years of experience building and shipping full-stack applications from zero to production in clinical or biomedical research environments, using React, TypeScript, and Next.js.
3+ years of experience in data science or computational research, working with large-scale data sets using distributed frameworks such as PySpark.
Demonstrated expertise in high-dimensional data analysis, including dimensionality reduction techniques (e.g., UMAP, PaCMAP, t-SNE) in oncology or genomics contexts.
Proven ability to own and architect end-to-end, data-intensive systems, making sound tradeoffs across frontend, backend, and data processing layers.
Strong experience designing scalable, secure backend systems and relational data models, particularly with PostgreSQL (Supabase experience is a plus).
Familiarity with modern genomics workflows and their application to precision oncology and clinical decision-making.
Track record of developing novel analytical methods for population-level clinical or genomic analysis, including establishing statistical rigor and confidence in results.
Comfortable operating in ambiguous, fast-moving environments, contributing to both technical architecture and product strategy.
Experience working in cross-functional teams, translating complex scientific requirements into intuitive, production-grade software.

Responsibilities

Own and evolve the platform end-to-end: drive design, architecture, and iteration of a production system supporting clinical and genomic research workflows.
Build high-performance full-stack applications: develop intuitive, scalable interfaces and services using React, TypeScript, and Next.js, enabling exploration of complex, high-dimensional datasets.
Architect data-intensive systems: design secure, scalable APIs and data models for clinical and genomic data using PostgreSQL (Supabase or similar) and AWS, balancing performance across client and server layers.
Develop and operationalize data pipelines: implement distributed workflows for large-scale clinical and genomic data using PySpark and related technologies.
Apply and extend advanced analytical methods: leverage dimensionality reduction and related techniques (e.g., UMAP, t-SNE, PaCMAP) to extract structure from high-dimensional biological data.
Drive novel research contributions: develop new approaches for analyzing population-level clinical and genomic patterns, with clear statistical grounding and practical relevance.
Bridge research and product: translate ambiguous scientific needs into well-defined product features, analytical tools, and user workflows.
Shape technical and product direction: contribute to architectural decisions, roadmap prioritization, and overall platform strategy in a dynamic environment.
Collaborate across disciplines: partner with researchers, clinicians, and engineers to ensure the platform delivers meaningful, actionable insights.