University Of Pittsburgh-posted 2 months ago
Full-time
Pittsburgh, PA
Educational Services

The University of Pittsburgh TRIADs lab is seeking a motivated Health Data Analyst to join a collaborative team investigating Parkinson's disease and related conditions. Our work leverages a large-scale retrospective dataset of 8 years of electronic health records (EHR) data covering nearly 600,000 patients. This role is an excellent opportunity for candidates seeking to contribute to cutting-edge health informatics research while building career pathways toward permanent employment. The analyst will play a key role in expanding and refining our existing research dataset, ensuring data quality, and supporting sub-projects focused on prediction of diagnosis and treatment patterns, clinical outcomes, and health services utilization. This position is designed as a full-time temporary role, with the possibility of conversion into a permanent staff position based on performance and funding.

  • Work with large-scale healthcare data (EHRs, clinical coding systems, structured and unstructured data).
  • Develop, validate, and maintain high-quality datasets to support multiple research projects.
  • Write efficient queries and scripts in SQL, and conduct statistical and exploratory analyses in R or Python.
  • Collaborate with faculty, data scientists, and clinicians to design and execute analysis plans.
  • Prepare data extracts and summaries tailored to project-specific needs.
  • Document data workflows and support reproducible research practices.
  • A Master's degree in Health Informatics, Biomedical Informatics, Data Science, Public Health, Biostatistics, Computer Science, or a related field (or equivalent professional experience).
  • At least 2 years of hands-on experience with SQL and one or more analysis languages (R, Python).
  • Prior experience working with healthcare data (EHR, claims, registries, or related sources).
  • Strong understanding of data quality principles and best practices in data curation.
  • Excellent communication skills and ability to work in a collaborative research environment.
  • Familiarity with clinical terminologies (ICD, SNOMED, RxNorm, LOINC).
  • Experience with large-scale data warehousing, high-performance computing, or cloud-based data platforms.
  • Knowledge of statistical modeling or machine learning approaches in healthcare.
  • Demonstrated ability to adapt quickly, learn new tools, and contribute innovative ideas.
  • Opportunity to contribute to high-impact Parkinson's disease research with direct clinical relevance.
  • Work within a leading academic research environment with exposure to interdisciplinary collaborations.
  • Competitive compensation with strong potential for conversion to a permanent position.
  • Professional development opportunities in advanced health informatics and data science.
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