Lab Data Coordinator (Full-Time)


Lab Data Coordinator

Fred Hutch - Seattle, Washington 


Cures Start Here. At Fred Hutchinson Cancer Research Center, home to three Nobel laureates, interdisciplinary teams of world-renowned scientists seek new and innovative ways to prevent, diagnose and treat cancer, HIV/AIDS and other life-threatening diseases. Fred Hutch’s pioneering work in bone marrow transplantation led to the development of immunotherapy, which harnesses the power of the immune system to treat cancer with minimal side effects. An independent, nonprofit research institute based in Seattle, Fred Hutch houses the nation’s first and largest cancer prevention research program, as well as the clinical coordinating center of the Women’s Health Initiative and the international headquarters of the HIV Vaccine Trials Network. Careers Start Here.

The Statistical Center for HIV/AIDS Research & Prevention (SCHARP) at the Fred Hutchinson Cancer Research Center in Seattle, WA is seeking an experienced and innovative Laboratory Data Coordinator to join the SCHARP Laboratory Data Operations (LDO) group. Part of the SCHARP Data Management Unit (DMU), the LDO team is responsible for developing and maintaining the laboratory assay and specimen data pipelines for multiple clinical trials, pre-clinical studies and research and development projects. SCHARP Lab Data Coordinators perform a variety of project and data management tasks related to specimen data pipelines from a number of clinical trials. The incumbent will be part of a team of data coordinators, data managers and programmers that oversee all SCHARP laboratory data pipelines and should be collaborative, yet self-directed and able to work independently in a fast-paced environment.


  • Serve as a liaison between SCHARP study teams and external collaborators to establish and monitor specimen data pipelines from clinical trials and associated specimen repositories
  • Develop and distribute standardized specimen data discrepancy reports; work with collaborators to investigate and resolve data discrepancies, troubleshoot issues; Identify opportunities for process improvements and collaborate to develop and implement solutions
  • Work with SCHARP programmers to develop specifications/requirements and perform routine testing of code and software developed for specimen data management
  • Work with SCHARP section representatives and external collaborators to develop and implement policies, SOPs, Work Practice Guidelines, and quality control methods
  • Act as a liaison between LDO and clinical research sites; represent LDO on SCHARP study teams and in internal or external meetings
  • Provide training and feedback to labs, clinical research sites and/or SCHARP staff
  • Serve as project manager for specimen data management initiatives and process evaluation/improvement projects
  • Learn and master skills in SAS, Access, Postgres, Unix/Linux, html or other languages/platforms to facilitate lab data management
  • Perform other responsibilities as required


Minimum qualifications:

  • Bachelor’s degree in biological sciences, biostatistics/statistics or equivalent
  • Minimum 2 years of practical data management experience
  • Experience utilizing common data management software like Excel or relational databases
  • Demonstrated ability to work independently and as part of a team
  • Demonstrated ability to manage multiple projects and competing priorities
  • Must be flexible, work well in a team environment, and be capable of meeting tight deadlines
  • Must be organized and detail-oriented, with excellent oral and written communication skills

 Preferred qualifications:

  • 2+ years of work experience, managing data in a scientific or health-related field
  • Experience managing data from clinical trials, preferably laboratory or specimen data
  • Familiarity with relational databases; design, development and/or database management
  • Working knowledge of laboratory information management systems, clinical data management systems, SAS, Postgres, CDISC and/or other clinical data standards
  • Demonstrated abilities to quickly and independently learn new technologies
  • Understanding of current/standard approaches to data collection, processing of raw data into analysis datasets, and other downstream research activities is highly desirable