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The Collaborative Health Studies Coordinating Center (CHSCC) is a non-profit, academic organization with over 20 years of experience running multi-site epidemiologic studies and clinical trials. Our center is a collaborative effort involving faculty, staff and students from the Departments of Biostatistics and Epidemiology at the University of Washington. Our team of programmers, biostatisticians, epidemiologists and project managers provides expertise in study design, data collection and management, and statistical analysis. Our mission is to support studies that further scientific inquiry in areas that will ultimately impact public health. We also support the next generation of researchers by offering assistantships to current students and postdoctoral fellowships to recent graduates. The CHSCC is physically located in beautiful Magnuson Park with free parking and is served by two bus routes with stops nearby.

The Department of Biostatistics has an outstanding opportunity for an experienced and proactive Data Manager to summarize data for tracking reports and develop analytic datasets for the Multi-Ethnic Study of Atherosclerosis Data Coordinating Center, an NHLBI-funded study of cardiovascular disease that started in 2000. MESA data is collected electronically in REDCap, enabling the data team to monitor data quality and consistency in real-time. The Data Manager will ensure that there is harmonized collection, cleaning, sharing and storage of data across MESA. The applicant should have an excellent understanding of data management, preferably from similar work in a multi-site collaborative research study. Ideal candidates should have solid experience with healthcare data and programming skills with SQL. We are seeking someone a resourcefulness, independent problem solver with excellent time management skills, attention to detail and the ability to negotiate and communicate priorities.

This research position is key to the success of the MESA study, a multi-cohort study in its 24th year of operation that has contributed over 2,100 scientific publications to date. The CHSCC in the Department of Biostatistics is high visibility in the research community at both the local and national levels and enjoys an excellent reputation as an outstanding center for research design and biostatistical analysis. The high quality of the CHSCC’s work helps to enhance the University’s research environment and in turn, helps to attract funding for further research studies. This active research environment attracts world-class faculty and students to the University and provides excellent training opportunities for students.
DUTIES AND RESPONSIBILITIES:

Work closely with Project Managers, Research Coordinators, and other staff to ensure the accuracy and consistency of data. Investigate and identify idiosyncrasies and fluctuations and make recommendations that support goals and objectives.

Resolve data discrepancies and database issues through coordination with the clinical team.

Consult with faculty and research scientists to interpret objectives and identify data needs.

Validate final data product through coordination with investigator.

Implement and maintain Data QC protocols and collaborate with study partners on Data QA/QC workflow efficacy.

Prepare interim and final analytic datasets and data documentation. Maintain and update study datasets and documentation on public access websites such as BIOLINCC and dbGaP.

Manage data access and sharing.

Present progress updates in weekly data team meetings and provide written summaries as needed.

Generate study reports and presentations as needed.

Manage data queries to Field Centers and other members of the study team via REDCap—generate queries, communicate issues to sites, track status and resolution, and generate summary reports.

Advise on case report form development and on dataset preparation. 10%

MINIMUM REQUIREMENTS

Bachelor's degree in a scientific, computing, or data-related field. Equivalent experience may substitute for degree.
Minimum 3 years of experience with data management in a related field using a Windows operating system.

ADDITIONAL REQUIREMENTS:

?Experience using relational databases (e.g. MS SQL Server, MS Access, REDCap).

Experience handling a high volume of diverse tasks in a timely manner with consistent accuracy and attention to detail.

Meticulous organizational skills and proven ability to multi-task and work independently and effectively in large, complex, multi-site, cross-functional teams.

Excellent work ethic and self-motivation.

Strong verbal and written communication skills with the ability to manage relationships and interact with a wide range of researchers and clinic staff.

Ability to complete complex data management tasks independently and to work in a group setting to meet project goals.

Equivalent education/experience will substitute for all minimum qualifications except when there are legal requirements, such as a license/certification/registration.

DESIRED QUALIFICATIONS:

Proficiency with Python, pandas, SQL server, or similar programming language.

Ability to use REDCap to design, conduct, and/or monitor data collection.

Experience with genetics data and ability to process large datasets.

Familiarity with human subjects research

Application Process:
The application process for UW positions may include completion of a variety of online assessments to obtain additional information that will be used in the evaluation process. These assessments may include Workforce Authorization, Cover Letter and/or others. Any assessments that you need to complete will appear on your screen as soon as you select “Apply to this position”. Once you begin an assessment, it must be completed at that time; if you do not complete the assessment you will be prompted to do so the next time you access your “My Jobs” page. If you select to take it later, it will appear on your "My Jobs" page to take when you are ready. Please note that your application will not be reviewed, and you will not be considered for this position until all required assessments have been completed.