Data Manager

Overview

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 Data Manager will support the Translational Research Program in Colorectal Cancer Disparities (TRPCD), housed at Fred Hutch Cancer Center, which leads several large, multi-institutional collaborative projects. This position is responsible for managing complex datasets, coordinating with scientists and collaborators, and supporting research activities to ensure smooth project execution. The Data Manager will also work closely with the Shared Resources laboratory to facilitate sample selection and provide key information for biospecimen collection, annotation, aliquoting, and distribution. This role requires strong technical, organizational, and communication skills to manage data repositories and contribute to ongoing research efforts.

Responsibilities

• Work closely with scientists, clinicians, shared resources lab personnel, biostatisticians, bioinformaticians, students, and postdocs to ensure seamless data integration and research coordination.
• Process, clean, and analyze large datasets using programming languages (R/Python)
• Create and maintain data dictionaries and codebooks.
• Manage biospecimen by implementing sample tracking protocols and creating and maintaining sample manifests
• Data integration and harmonization through medical chart abstraction, harmonizing data across centers, and working with cancer registries for intake.
• Prepare and present data updates to investigators.
• Ensure documentation and compliance by maintaining version control through GitHub, developing and updating standard operating procedures (SOPs) for data/sample management, and monitor compliance with data security protocols.
• Technical operations including executing Excel activities, maintaining database systems, troubleshooting issues, and ensuring data backup and security.
• Generating progress reports, attending team meetings/presentations, train team members on data management procedures, and document workflow processes.
• Implement quality control measures, monitor data integrity, perform regular audits of data systems, and ensure compliance with institutional standards.
• Other duties as assigned.

Qualifications

MINIMUM QUALIFICATIONS:

• Bachelor’s Degree or equivalent experience in Biostatistics, Data Science, Epidemiology, Bioinformatics, Biorepository Science, or a related field.
• Two (2) years of relevant experience.
• Data Management & Analysis
  • Proficiency in R and Python for data processing, cleaning, and analysis.
  • Experience with handling of large-scale datasets, including clinical and experimental data
  • Ability to standardize and harmonize data across multiple sites and formats.
  • Familiarity with cloud-based storage solutions (e.g. AWS, Google Drive, OneDrive) for data sharing and collaboration.
• Sample Management & Biorepository Oversight
  • Experience managing and maintaining both physical and virtual biospecimen repositories.
  • Deep understanding of sample tracking, quality control (QC), and lab protocol best practices.
  • Experience with integrating sample metadata with clinical and molecular datasets.
• Data Harmonization
  • Expertise with REDCap
  • Ability to harmonize clinical and epidemiological data across centers and studies
• Project Coordination and Communication
  • Ability to coordinate across multiple institution