Clinical Research Data Analyst III

Day-to-day responsibilities may include:

• Extracting and managing data from institutional data warehouses.
• Developing, maintaining, and documenting high-quality, reusable queries and data pipelines.
• Translating complex research questions into structured data specifications and analytic workflows.
• Collaborating with CTSI informatics and research teams to support grant-funded and investigator-initiated studies.
• Contributing to data governance, validation, and QA processes that ensure regulatory compliance.
• Supporting systems integrations that enhance business workflows, including Git, Salesforce, and REDCap.
• Participating in process improvement initiatives that advanceteam efficiency and data quality.
• Meet with research teams to map study requirements into clear data specifications.
• Produce scope-of-work documents, including timelines and effort estimates.
• Execute SOWs through data extraction, QA, analysis, and documentation.
• Communicate progress and findings to research partners throughout the project.
• Support ongoing development of our data platforms, tools, and workflows.
• Contribute to CTSI research, innovation, and operational initiatives as assigned.

• Master’s degree in data science, computer science, health informatics, or a related field.
• 3+ years of experience working with healthcare, biomedical, medical device, or clinical research data in an analyst role.
• Proficiency in SQL for querying large relational databases.
• Experience with programming languages for data analysis (Python, R, and/or Julia).
• Experience with Git/GitHub for version control.
• Strong attention to detail, data validation, and quality assurance.
• Excellent communication skills with the ability to collaborate with both technical and non-technical stakeholders.
• Experience with large language models or NLP in a biomedical context.
• Experience with Epic Clarity/Caboodle, Databricks, and cloud-hosted data platforms.
• Familiarity with clinical data standards such as FHIR, OMOP, and i2b2.
• Knowledge of HIPAA, human subjects protections, and clinical research regulations.
• Experience working in an academic medical center or CTSI environment.
• Active clinical experience or clinical domain knowledge.
• Experience with Epic data models, OHDSI toolsets, the OMOP CDM, and SQL on Databricks will make an applicant stand out. Experience with biomedical NLP and clinical practice is also highly valued.