Health Data Analyst na University of Pittsburgh

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.

Position Overview

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.

Responsibilities

- 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.

Qualifications

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.

Preferred Skills

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.

Why Join Us?

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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