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# Data Analyst 1

- **Company:** Brigham and Women's Hospital
- **Location:** Boston, MA, United States
- **Salary:** $53,040.0 - $75,889.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Bioinformatics, Health Informatics, Computational Biology, Computer Simulation, Data Cleansing, Data Visualization, Linux, R (Programming Language), Python (Programming Language), Machine Learning
- **Published:** October 14, 2026
- **Apply:** https://jobs.localjobnetwork.com/apply/add/88628977/1

## About the Role

Candidates should have a master's degree in bioinformatics, computational biology, genomics, computational genomics, biomedical informatics, biostatistics, data science, or a closely related quantitative field, with experience in the computational analysis of large-scale biological or biomedical datasets.

Candidates should have:

 * Proficiency in R and Python for biomedical data analysis.

 * Experience working in Linux/Unix environments and with large or high-dimensional datasets.

 * Experience with bioinformatics workflows, statistical analysis, data visualization, and reproducible computational methods.

 * Strong quantitative, analytical, and problem-solving skills.

 * Ability to write clear, efficient, well-documented, and reproducible code.

 * Strong attention to detail and commitment to data quality, scientific rigor, and research integrity.

 * Ability to troubleshoot analytical and computational problems independently and develop effective solutions.

 * Strong organizational and time-management skills, with the ability to manage multiple projects and priorities.

 * Excellent written and oral communication skills, including the ability to communicate analytical findings to investigators from diverse scientific backgrounds.

 * Ability to work both independently and collaboratively within a multidisciplinary research environment. * Initiative, adaptability, and intellectual curiosity in applying computational approaches to clinically

relevant biomedical questions.

Prior experience in COPD or pulmonary research is not required.

## Description

The Data Analyst will work closely with Dr. El Boueiz and a multidisciplinary team of geneticists, genetic epidemiologists, biostatisticians, computational biologists, translational scientists, and clinicians. The role will involve substantial responsibility for the design, execution, interpretation, and documentation of computational analyses and the development and implementation of bioinformatics approaches across ongoing research projects.

Responsibilities

 * Manage, process, and analyze large-scale genetic, genomic, transcriptomic, proteomic, imaging, and clinical datasets.

 * Develop, implement, and maintain reproducible bioinformatics and computational workflows using R, Python, Linux/Unix, and related tools.

 * Perform data preprocessing, quality control, harmonization, integration, statistical analysis, and visualization across multiple data types and research cohorts.

 * Apply bioinformatics, statistical genetics, multi-omics, systems biology, and machine-learning methods to investigate COPD and related pulmonary phenotypes.

 * Integrate multimodal data to identify biomarkers and molecular subtypes and investigate disease mechanisms and potential therapeutic targets.

 * Evaluate and interpret analytical findings in collaboration with investigators within their biological and clinical context.

 * Review relevant scientific literature to identify and implement appropriate analytical and computational methods for specific research questions.

 * Generate publication-quality figures, tables, and visualizations for manuscripts, abstracts, presentations, and grant applications.

 * Maintain clear and reproducible documentation of datasets, analytical methods, code, software environments, workflows, and results.

 * Troubleshoot computational and analytical challenges and develop, optimize, and validate analytical pipelines.

 * Present analytical results at research meetings and contribute substantively to scientific abstracts, conference presentations, manuscripts, and grant-related analyses.

 * Manage multiple projects and analytical priorities while meeting research milestones and deadlines.