- Salary
- $53k – $76k
- Location
- 221 Longwood Avenue Boston (Eugene Braunwald Research Center), United States of America
- Workplace
- Hybrid
- Type
- Full-time
- Source
- Workday
Description
Mass General Brigham relies on a wide range of professionals, including doctors, nurses, business people, tech experts, researchers, and systems analysts to advance our mission. As a not-for-profit, we support patient care, research, teaching, and community service, striving to provide exceptional care. We believe that high-performing teams drive groundbreaking medical discoveries and invite all applicants to join us and experience what it means to be part of Mass General Brigham.
Job Summary
The Channing Division of Network Medicine at Brigham and Women’s Hospital is seeking a highly motivated Data Analyst to join the research group led by Dr. Adel El Boueiz within the Systems Genetics and Genomics Unit. The successful candidate will contribute to computational studies of chronic respiratory diseases, particularly chronic obstructive pulmonary disease (COPD) and related pulmonary phenotypes, by integrating genetic, genomic, transcriptomic, proteomic, imaging, and clinical data from large, deeply phenotyped cohorts. Projects will apply statistical genetics, bioinformatics, multi-omics integration, systems biology, and machine learning to identify biomarkers and molecular subtypes, elucidate disease mechanisms, and prioritize potential therapeutic targets.
Qualifications
Research Environment
Brigham and Women’s Hospital is a major teaching hospital of Harvard Medical School and an international leader in biomedical research and clinical care.
The Channing Division of Network Medicine is a research division within the Department of Medicine that integrates epidemiologic, genomic, computational, and systems biology approaches to investigate the mechanisms of complex human diseases.
The Division brings together multidisciplinary expertise in epidemiology, biostatistics, bioinformatics, genetics, epigenetics, transcriptomics, proteomics, metabolomics, metagenomics, imaging, and network medicine.
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.
Qualifications
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.
Additional Job Details (if applicable)
Remote Type
Work Location
Scheduled Weekly Hours
Employee Type
Work Shift
Pay Range
$53,040.00 - $75,888.80/Annual
Grade
5
EEO Statement:
Mass General Brigham Competency Framework
At Mass General Brigham, our competency framework defines what effective leadership “looks like” by specifying which behaviors are most critical for successful performance at each job level. The framework is comprised of ten competencies (half People-Focused, half Performance-Focused) and are defined by observable and measurable skills and behaviors that contribute to workplace effectiveness and career success. These competencies are used to evaluate performance, make hiring decisions, identify development needs, mobilize employees across our system, and establish a strong talent pipeline.