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Lab Data Coordinator

Fred Hutchinson Cancer Research Center
Seattle, WA

Job ID 6496


Fred Hutchinson Cancer Research Center, home of three Nobel laureates, is an independent, nonprofit research institution dedicated to the development and advancement of biomedical research to eliminate cancer and other potentially fatal diseases. Recognized internationally for our pioneering work in bone-marrow transplantation, the five scientific divisions at Fred Hutch collaborate to form a unique environment for conducting basic and applied science. Fred Hutch, in collaboration with its clinical and research partners, the University of Washington and Seattle Children’s, is the only National Cancer Institute-designated comprehensive cancer center in the Pacific Northwest. Join us and make a difference!

About the Division & Research Program:

The Vaccine and Infectious Disease Division (VIDD) was established as an institute at Fred Hutch in 2007 to facilitate and enhance the Hutch’s efforts in infectious disease prevention and vaccine development. The institute achieved Division status in 2010 and now has more than 50 faculty members and houses the HIV Vaccine Trials Network (HVTN) – the world’s largest clinical trials network for the development and testing of an HIV vaccine.

Biostatistics, Bioinformatics, & Epidemiology (BBE) is a research program within the Vaccine and Infectious Disease Division of the Fred Hutch. With the goal being to eliminate the mortality and morbidity of infectious diseases, members of the program conduct quantitative scientific research employing biostatistics, bioinformatics, computational biology, infectious disease epidemiology, and mathematical modeling. Members of the program collaborate extensively with laboratory and clinical science colleagues both within the Hutch and provide leadership for statistical data management centers and modeling consortia worldwide.


As part of the BBE program in VIDD, The Statistical Center for HIV/AIDS Research & Prevention (SCHARP) provides statistical collaboration to infectious disease researchers around the world and conducts a complementary program of statistical methodology, and mathematical modeling research. SCHARP also collects, manages, and analyzes data from clinical trials and epidemiological studies dedicated to the elimination of infectious disease as a threat to human health. Current projects include studies to evaluate and implement prevention strategies for HIV, tuberculosis, polio, malaria and other globally important pathogens.

Job Summary:

We are looking for 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. Primary projects include managing lab data from studies implemented by the HIV Vaccine Trials Network (HVTN), HIV Prevention Trials Network (HPTN), Microbicides Trials Network (MTN) and the Collaboration for AIDS Vaccine Discovery (CAVD). 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.


In support of research network operations, funding agency requirements, and organizational needs, the Lab Data Coordinator may perform some or all of the following tasks:

  1. 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
  2. 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
  3. Work with SCHARP programmers to develop specifications/requirements and perform routine testing of code and software developed for specimen data management
  4. Work with SCHARP section representatives and external collaborators to develop and implement policies, SOPs, Work Practice Guidelines, and quality control methods
  5. Act as a liaison between LDO and clinical research sites; represent LDO on SCHARP study teams and in internal or external meetings
  6. Provide training and feedback to labs, clinical research sites and/or SCHARP staff
  7. Serve as project manager for specimen data management initiatives and process evaluation/improvement projects
  8. Learn and master skills in SAS, Access, Postgres, Unix/Linux, html or other languages/platforms to facilitate lab data management
  9. 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

Please include a cover letter when applying for this position either as an additional attachment on your profile or merged into the file that contains your resume.

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