Position Title: Clinical data manager

Duties & Responsibilities: SUMMARY The general objective of this position is to provide data management support to basic science and clinical investigators at CWRU/UH on both small and large research projects. In this role, the Research Associate will serve as the lead clinical data manager on transdisciplinary research teams. Specifically, the Research Associate will be expected to write a preliminary plan for data management for inclusion in grant applications, including development of appropriate budgets and timelines. During study initiation, the Research Associate will: 1) develop, test, and refine case report forms; 2) participate in the specification, design, development, and testing of relational databases; and 3) write documentation regarding data management plans. The Research Associate will also be highly skilled in R, SAS (e.g., SAS datastep and SAS macros) and SQL programming and will be responsible for developing programs to respond to data queries, perform regular monitoring of study progress and data quality, and perform any relevant data cleaning tasks. Once data from a study has been collected and appropriately cleaned, the Research Associate will work closely with study statisticians to generate analytic data sets. The Research Associate will also be expected to mentor junior clinical investigators with regard to data management programming and appropriate data management practices. RESPONSIBILITIES A. Proposal Development: The Research Associate will collaborate with appropriate study personnel to develop and write an appropriate data management plan that will be included in grant applications, including the development of an appropriate budget and timeline. B. Case Report Form Generation: The Research Associate will collaborate with appropriate study personnel to develop, test, and refine clear, consistent, and complete case report forms (CRFs). This may include development of appropriate training documentation for CRFs for inclusion in operations manuals. C. Database Development and Data Management Documentation: The Research Associate will either design and develop databases themselves or work with database developers to participate in the specification, design, development, and testing of relational databases. The Research Associate will also work with appropriate study personnel to ensure that there is appropriate up-to-date documentation describing the relevant databases (such as data dictionaries, codebooks, and procedures for loading non-CRF data into databases) and data management procedures (such as data entry instructions and procedures for data monitoring). D. Data Monitoring and Cleaning: The Research Associate will write programs to: 1) produce regular queries based on validation checks or errors identified during data entry; 2) summarize study progress and data quality that is then sent to appropriate study personnel or external entities; 3) Score any validated instruments used in a study, which may involve a review of the literature; and 4) Merge data obtained from several different sources. The Research Associate will also coordinate the resolution of any outstanding data entry errors to ensure the database is appropriately updated and if appropriate, will modify study procedures to prevent future errors. E. Mentoring: The Research Associate will be expected to provide informal mentorship to junior clinical investigators, residents, fellows, and content-area graduate students with regard to clinical data management. This will involve participation in weekly office hours and may involve participation with relevant groups in the CTSA national consortium, of which the Cleveland CTSC is a member.

Position Qualifications: EDUCATION This position requires a Master’s degree in a related field (e.g., informatics, computer science, public health, statistics, epidemiology). EXPERIENCE This position requires at least 1 year of experience as a clinical data manager in a biomedical research environment, preferably within a hospital or university setting. SKILLS A. Basic understanding of the clinical research process; familiar with different study designs, statistical analysis, and common issues encountered in research. B. Expert knowledge of the data management role in clinical research. C. Strong knowledge of case report form development. D. Strong knowledge of data reporting and visualization. E. Strong knowledge of statistical programming techniques, with functional mastery of R, SAS, and SQL. Knowledge of LaTeX and Sweave/KnitR for R is particularly appealing. F. Strong knowledge of relational databases. Working knowledge of REDCap and MySQL. G. Familiarity with Linux (preferably CentOS / RedHat Enterprise Linux). Working knowledge of command line interface for Linux. H. Basic knowledge of Linux server system administration, including user management, firewall configuration, cron scheduling, and bash scripting. Knowledge of Python preferred, but not required. I. Basic understanding of web development, including knowledge of HTML/CSS. Knowledge of PHP and Javascript preferred, but not required. J. Basic understanding of encryption, data security, and data redundancy. K. The ability to juggle and prioritize several complex projects simultaneously. L. Detail oriented. M. Ability to identify problems and solve them pragmatically. N. Highly organized, with the initiative, confidence, decisiveness, and technical aptitude to work with limited or no supervision. O. Excellent interpersonal skills and the desire and ability to be a strong team member within diverse research teams. P. Sound communication skills, both oral and written. TECHNICAL SKILLS A. Strong knowledge of statistical programming techniques, with functional mastery of R, SAS, and SQL. Knowledge of LaTeX and Sweave/KnitR for R is particularly appealing. B. Strong knowledge of relational databases. Working knowledge of REDCap and MySQL. C. Familiarity with Linux (preferably CentOS / RedHat Enterprise Linux). Working knowledge of command line interface for Linux. D. Basic knowledge of Linux server system administration, including user management, firewall configuration, cron scheduling, and bash scripting. Knowledge of Python preferred, but not required. E. Basic understanding of web development, including knowledge of HTML/CSS. Knowledge of PHP and Javascript preferred, but not required.

Salary Range: Commensurate with experience

Benefits:

Web Site: http://cci.case.edu/cci/index.php/Main_Page

Application Address: Denise Babineau, PhD Assistant Professor Director, CCI Statistical Sciences Core

Contact Email: denise.babineau@case.edu

Application Deadline: 12/01/2012