Clinical Research Data Analyst (Informatics)
The University of California, San Diego
About this position
Position Description
The Alzheimer's Disease Cooperative Study (ADCS) is a progressive, multi-site clinical research consortium created to provide an operational framework for Alzheimer’s disease clinical trials and research projects. It was formed in 1991 as a cooperative agreement between the National Institute on Aging (NIA) and the University of California, San Diego and has since served as a cornerstone of Alzheimer’s disease clinical research across the country. The ADCS promotes the discovery, development, and testing of new drugs, natural products, and lifestyle interventions for the treatment or prevention of Alzheimer’s disease, particularly those that are novel or in a proof-of-concept stage. The ADCS infrastructure includes expertise in study design and conduct, and full clinical trial management capabilities through our coordinating center and network of 50+ research sites that participate in studies coordinated by the ADCS. The ADCS provides expertise in developing Alzheimer's disease protocols, recruitment, and management of multiple clinical trials or prospective cohort studies of varying sizes and complexity as a coordinating center as well as a site. The ADCS has a robust program in large data projects and informatics involving secondary data analysis, harmonization, and emulated trials using electronic health records (EHR). The mission of the ADCS research program is accomplished with a diversified funding portfolio, ranging from federal funding such as NIH, to Industry Partners, Foundations, and Gifts. The Clinical Research Data Analyst is responsible for delivering informatics and data management activities in a complete, consistent, accurate and high quality manner for assigned studies. Works collaboratively with Clinical Research Scientists, Clinical Operations, Biostatistics and others to meet study deliverables and timelines. The Clinical Research Data Analyst may act as the Data Management Lead on projects where required. Supports target trial emulation (TTE) clinical research studies by developing and validating database queries within the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). This work will identify eligible cohorts, define exposure and outcome variables, establish time zero, and generate reproducible evidence analyses. Works on research data reporting assignments that are of moderate diversity in scope. Exercises judgment within generally defined practices and policies in selecting methods and techniques for obtaining solutions. Provides data listings and metrics as requested by clinical and project teams. Accesses, reviews, analyzes, validates and maintains confidential clinical research data ensuring consistency, integrity and accuracy. Develops and issues database queries within electronic health records (eHR) data to produce results that are consistent with the project Statistical Analysis Plan. Assists in data transfer activities and performs vendor data reconciliation. Develops clinical research plans, user requirements, and quality check specifications and implementations. Facilitates User Acceptance Testing (UAT) prior finalizing solutions and makes update changes as needed. Interacts with, understands, and can reproduce clinical data standards models, especially OMOP. Professional who applies acquired job skills, policies, and procedures to complete substantive assignments / projects / tasks of moderate scope and complexity; exercises judgment within defined guidelines and practices to determine appropriate action.
Qualifications
Six (6) years of relevant experience or a Bachelor's in a related field plus two (2) years of experience. Working knowledge of research function. Working skills in statistical analysis, systems programming, database design and data security measures. Working skills in analysis and consultation. Experience with statistical and data management programming (Python, R, SQL) and the use of statistical software skills for database management, quality assurance and data analysis in a Linux terminal (Bash) environment Skills to communicate complex information in a clear and concise manner both verbally and in writing. Expert understanding of relational and object oriented databases, data and file types, and user interface design. Experience in clinical research informatics and some Electronic Health Records (eHR) systems (Databricks, Epic). Knowledge of GCP and 21 CFR Part 11 requirements regarding regulated documentation and software. Working knowledge of medical terminology, medications, clinical research terminology, and healthcare data standards and terminologies, including MedDRA, WHO Drug, CDISC, OMOP, LOINC, SNOMED, ICD, RxNorm, HL7, and FHIR. Excellent organizational and problem solving skills; strong attention to detail but ability to plan for long-term contingencies. Proven ability to research, gather and organize information to produce clear and concise reports and presentations using various resources.