Data Scientist I - Genetics Analysis

Location US-MA-Roslindale
Job ID 2023-1249
Position Type
Regular Full-Time


Biomedical researcher with specialized training in quantitative methodology. Manages, cleans, manipulates, and analyzes data in the service of the advancement of research and maintenance of group operations. Experience with one or more data types including next-generation sequencing, genome-wide associations, epigenetics, transcriptomics, or proteomics is required. Designs and implements reusable bioinformatics analysis pipelines for processing genetics/genomics data and integrates computational methods/pipelines within high performance computing clusters. Experience with cloud-computing is ideal. Constructs visualizations to depict trends and associations, conducts exploratory data analyses, and develops reports and summaries to communicate results to colleagues. Works within a biomedical research team to facilitate the production of scientific work product (e.g. design and execution of studies or experiments, as well as publication and dissemination of findings). Develops and applies algorithms for summary and analysis of complex data structures. Conducts statistical analysis for assessment of association and in service of causal inference. Participates in the design and development of custom software to facilitate analysis of biomedical research data and/or big data derived from research or administrative sources. Provides data analytic support to ongoing observational and interventional studies, and leads or participates in analyses of secondary data structures ranging from modest to very large size. Supports the development of funding applications and provides on-demand assistance with data analysis and interpretation.

Requires familiarity with statistical analysis, software development, visualization, algorithm development, supervised and unsupervised learning, predictive analytics. Advanced skills in data management, manipulation, and summarization are critical, and skills in natural language processing are a plus. Existing, or ability to develop, comfort with rigorous version control and the principles of reproducible research are required. The ability to work in a team-based research environment is essential.


Provide data management, manipulation, cleaning, and analysis support for biomedical research projects. Participate in development of algorithms and software tools facilitating scientific productivity and project completion. Generate analysis pipelines and automated functions for repetitive summaries and analyses. Develop and present reports of analytic findings to internal and external investigators and teams. Support the development of abstracts, manuscripts, and funding applications under the direction of the Investigators. Prepare tabular, graphical, and narrative summaries of findings of publication quality.

Required Qualifications

  • Requires a Master’s degree in a quantitative biomedical science field such as bioinformatics; biostatistics; quantitative epidemiology; statistical genetics; econometrics or systems biology; data science; and 0-3 years’ experience as a professional quantitative scientist. Additional experience relevant to specific projects may be required.
  • Knowledge of and experience with statistical and quantitative modeling (regression / GLM / GAM, simulation, cluster analysis, neural networks, decision trees, bagging, boosting etc.); experience with one or more programming languages. Specialized training and experience more than one quantitative programming languages (R/Python/SAS/Matlab), with excellent facility in at least one language is essential. Experience with database technologies (SQL, REDCap) is advantageous. Experience with web services and distributed computing tools is preferred. Experience using high performance computing systems running LINUX or UNIX OS and experience with Cloud-computing platforms such as Amazon Web Services (AWS) or Google Cloud are a plus.
  • The ability to acquire new knowledge and skills to be able to perform analytical tasks using newly developed statistical methods/tools is of utmost importance. A passion for work in biomedical science and experience in aging research is preferred. Applicants should have the ability to work simultaneously on multiple projects with strict attention to detail, ability to work independently as well as part of a team, as well as superb oral and/or written English language skills.


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