Fred Hutchinson Cancer Research Center

Data Scientist III

Pharmaceuticals & Biotech
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Master's or PhD in Bioinformatics, Statistics, Biostatistics, Mathematics, Computer Science, or Physics with 2 years of experience.
  • Core competency in genomics, natural language processing, image processing, or medical records.
  • Proficient in R and Python programming languages.
  • Experience in statistical analysis, machine learning, and predictive modeling.
  • Familiarity with data formats like XML and JSON, and markup languages.
  • Experience with Unix/Linux and distributed computing environments.
  • Proficiency in visualization software such as Shiny and JavaScript.
  • Experience with code version control systems (Git) and containers (Docker).

Responsibilities

  • Integrate diverse data sources, including clinical, genomic, and imaging-derived data.
  • Develop machine learning algorithms and predictive models to enhance cancer research.
  • Deliver actionable insights to support cohort definition and dataset standardization.
  • Identify opportunities for growth in the data science initiative.
  • Collaborate with researchers to translate research questions into data products and tools.
  • Manage data science projects while ensuring data security and compliance standards.
  • Communicate findings effectively to both technical and non-technical audiences.

Benefits

  • Comprehensive medical, vision, and dental insurance.
  • Flexible spending accounts for healthcare and dependent care expenses.
  • Life and disability insurance.
  • Retirement savings plans with company contributions.
  • Family life support services and employee assistance program.
  • Onsite health clinic for convenient access to care.
  • Tuition reimbursement for continued education.
  • Generous paid vacation and sick leave policy.
  • Paid parental leave for new parents.
Full Job Description
Overview

The Translational Data Scientist III develops, curates, and analyzes multimodal research datasets that integrate clinical, genomic, and other translational data modalities. This role focuses on building analytically ready datasets and supporting collaborative translational research projects under the guidance of senior scientific and technical leadership.

Working closely with the Translational Data Science Staff Scientist, this position contributes to data harmonization, cohort construction, and cross-domain integration using institutional data platforms and modern data engineering practices. The role emphasizes technical development, structured learning, and applied collaboration with research teams and program level efforts.

This is a hands-on technical role situated at the interface of translational science, data engineering, and research collaboration. This role builds data science solutions, applying LLMs/AI to process, structure, and contextualize health data, and creating data products that are customize to the needs of our translational research programs at Fred Hutch including Clinical trials, Precision Oncology, disease-focused programs, and new data science capabilities both at Fred Hutch and across institutions via the Cancer AI Alliance.

Responsibilities

  • Identify and integrate disparate data sources, both internal and external, including clinical data, genomic data, imaging-derived data, and well-established, publicly available databases.
  • Develop and deploy machine learning algorithms, predictive models, and classification methods to advance cancer research and inform clinical decision making, applying reproducible data processing practices within cloud-based analytic environments.
  • Deliver novel, data-driven insights to improve outcomes in the treatment of cancer, supporting cohort definition, feature engineering, and dataset standardization.
  • Identify areas of growth for the data science initiative and actively engage in enhancing the breadth and reach of data science across the Fred Hutch campus.
  • Collaborate with faculty collaborators, researchers and clinicians to identify high-impact opportunities for data science applications, translating research questions into structured data products and tools
  • Manage data science projects from creation to completion, following established practices for data security, privacy, and compliance.
  • Communicate results to technical and non-technical audiences, contributing to documentation of datasets, assumptions, and transformation logic.


Qualifications

MINIMUM QUALIFICATIONS:
  • Master's or PhD degree in Bioinformatics, Statistics, Biostatistics, Mathematics, Computer Science, Physics, or equivalent required, with a minimum of two years of related experience.
  • Core competency in at least one of the following: genomics, natural language, image processing, medical records or claims.
  • Proficiency in R or Python.
  • Knowledge of statistical analysis, machine learning and predictive modeling.
  • A variety of data formats and markup languages (e.g. XML, JSON, RMarkdown).
  • Unix/Linux and distributed computing.
  • Visualization software: Shiny, Javascript, D3.
  • Code version control (Git, Github) and containers (Docker).
  • Proficiency in at least one common object-oriented programming language (e.g. Java, C++, C#).
  • Experience in application development, visualization, and user design.

PREFERRED QUALIFICATIONS:
  • 3-5 years of related experience.
  • Experience working with clinical, genomic, imaging or other biomedical research data, ideally in Databricks or similar platform.
  • Demonstrated experience using Python, R, or SQL for data analysis and transformation.
  • Familiarity with structured data models and relational data environments.
  • Understanding of reproducible research or analytic workflows.
  • Ability to work collaboratively across scientific and technical teams.
  • Strong organizational and documentation practices.
  • Exposure to clinical data models such as OMOP or similar standardized healthcare data structures.
  • Experience working in a translational research or academic medical environment.
  • Familiarity with cloud-based research computing environments.
  • Experience supporting collaborative research projects or shared data resources.

The annual base salary range for this position is from $126,984 to $200,678, and pay offered will be based on experience and qualifications. This position may be eligibile for relocation assistance.

Although Fred Hutch is not sponsoring most H-1B visas at this time, candidates who already hold an H-1B sponsored by another organization and are currently in the U.S. may be eligible for this position.

Fred Hutchinson Cancer Center offers employees a comprehensive benefits package designed to enhance health, well-being, and financial security. Benefits include medical/vision, dental, flexible spending accounts, life, disability, retirement, family life support, employee assistance program, onsite health clinic, tuition reimbursement, paid vacation (12-22 days per year), paid sick leave (12-25 days per year), paid holidays (13 days per year), and paid parental leave (up to 4 weeks).

Additional Information

About Fred Hutchinson Cancer Research Center

The Fred Hutchinson Cancer Research Center is a non-profit research institute dedicated to the prevention, treatment, and cure of cancer, HIV/AIDS, and other diseases. It was founded in 1975 by Dr. William Hutchinson in honor of his brother Fred, who died of lung cancer at the age of 45. The center is located in Seattle, Washington and employs over 3,000 scientists, physicians, and staff. It is one of the largest and most respected cancer research centers in the world, and has made significant contributions to the development of bone marrow transplantation and other cancer treatments.
Learn more about Fred Hutchinson Cancer Research Center
Size
3,000 employees
Industry
Founded
1975

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