Research Data Analyst

Brown Medicine

1d • $82,285 - $135,782 • Onsite

About The Position

Reporting to the Manager, Research Data, the Research Data Analyst is the primary analyst for building out Brown University Health’s research data ecosystem: a secure cloud environment that integrates, curates, and validates clinical and research data, supports cohort identification, and provides governed, standardized access for investigators and external partners.

The Analyst owns the ontologies, vocabularies, and metadata that make research data understandable and usable. The role focuses on transforming ingested data into i2b2 or a similar common data model, mapping local source data to standard clinical terminologies, and documenting data definitions, origins, and derivations. The Analyst may later support extending the environment to other data models such as OMOP.

This is a hands-on role with substantial ownership. The Analyst drives analytic work within the processes, roadmap, and vision established by the Manager, Research Data, the Director, Data Architecture, and the Chief Data and Analytics Officer. The role collaborates closely with investigators, the research facilitation group, and technical staff building the research data ecosystem. The position is grant funded for five years, with the intent to transition to additional funding thereafter.

Requirements

• Bachelor's degree in Biomedical or Clinical Informatics, Health Information Management, Computer Science, Data Science, Epidemiology, Biostatistics, Public Health, or a related quantitative field.
• At least 4 years of hands-on data analysis experience in an academic medical center, healthcare organization, biomedical research, or life sciences environment, including direct work with clinical or electronic health record data.
• Advanced SQL skills, including complex multi-table queries, transformations, views, and performance tuning on large clinical data sets using platforms such as Snowflake, SQL Server, PostgreSQL, or Oracle.
• Strong understanding of clinical terminologies such as SNOMED CT, ICD-10-CM, LOINC, RxNorm, CPT, and UMLS, including hierarchies, mappings, and versioning.
• Experience working with electronic health record data and its complexities for research or analytics.
• Demonstrated ability to own analytic work from requirements through delivery with limited day-to-day supervision.
• Strong attention to detail and documentation habits, with the ability to explain data definitions and limitations clearly to researchers and non-technical audiences.
• Equivalent combinations of education and relevant professional experience may be considered in accordance with Brown University Health requirements.

Nice To Haves

• Master's degree in Biomedical Informatics, Epidemiology, Biostatistics, Public Health, Data Science, or a related field.
• Hands-on experience with i2b2 or OMOP, including loading data into the model, ontology or vocabulary build-out, and cohort discovery tools such as the i2b2 web client or ATLAS.
• Prior experience as a researcher, research analyst, or research coordinator on funded studies, including familiarity with the research lifecycle from protocol through publication.
• Working knowledge of research data frameworks, including common data models, cohort discovery, FAIR data principles, and observational and retrospective research.
• Understanding of research data governance, including IRB processes, data use agreements, HIPAA de-identification, limited data sets, and access controls.
• Experience with Epic Clarity or Caboodle.
• Proficiency in Python or R for data parsing, profiling, and validation.
• Experience with modern cloud data platforms.

Responsibilities

• Design, build, and maintain i2b2 or similar common data model ontologies, including hierarchies, local concepts, synonyms, code crosswalks, and terminology version updates.
• Map local, non-standard source codes to standard clinical terminologies, including SNOMED CT, ICD-10-CM, LOINC, RxNorm, and CPT.
• Develop and maintain metadata for data ingested into the research data environment, including data dictionaries, source-to-target mappings, mapping provenance, data lineage, and plain-language definitions for researchers.
• Write, test, and optimize SQL transformations that move ingested source data into i2b2 fact and dimension tables or a similar common data model, working within ingest pipelines operated by Data Architecture & Analytics.
• Validate the completeness, accuracy, and longitudinal consistency of research data through profiling and quality checks; investigate and resolve data-quality issues with source system owners.
• Apply data governance requirements, including confirming IRB approvals and data use agreements, minimum-necessary data delivery, de-identified and limited data set standards, and documentation supporting accounting of disclosures.
• Identify recurring requests and common definitions that could become reusable data products, standard concept sets, or self-service capabilities, and recommend them to the Manager, Research Data for roadmap prioritization.
• Perform other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level