Data Scientist II ( Omics) - Roslindale
Overview:
The Marcus Institute for Aging Research seeks a Biomedical researcher with expertise in applying statistical and quantitative modeling approaches and with experience in genetics/genomics (‘omics’) data applications. Manages, cleans, manipulates, and analyzes omics data (genomics, epigenomics, gene expression, proteomics, metabolomics and microbiome) in the service of the advancement of research conducted on multiple complex phenotypes.Designs, implements, and maintains reusable bioinformatics analysis pipelines for processing omics data and integrates computational methods/pipelines within high performance computing clusters. Experience with cloud-computing is ideal. Constructs visualizations to depict 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 a variety of omics data.
Conducts statistical analysis for assessment of association and in service of causal inference. Participates in customizing software to facilitate analysis of omics research data. Provides data analytic support to ongoing studies requiring 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. Participates in education and peer mentoring of clinical colleagues.
Responsibilities:
- Provide data management, manipulation, cleaning, and analysis support for omics research projects.
- Develop and present reports of analytic findings to internal and external investigators and teams.
- Present work to internal and external parties.
- Prepare tabular, graphical, and narrative summaries of findings suitable for publication.
- Support the development of abstracts, manuscripts, and funding applications under the direction of the Investigators.
- Implement cutting-edge and newly developed algorithms and software tools for analyzing multidimensional omics data, either independently or as part of a team, within a reproducible research environment.
- Building analysis workflows/pipelines and automated functions for repetitive summaries and analyses.
- Maintain and manage coding libraries and team resources in line with advanced standards.
- Provide expertise in statistical analysis and bioinformatics function on small to intermediate-scale projects.
- Present technical aspects of development to the research team.
- Participate in the development of funding applications to drive future work.
Required Qualifications:
Requires a Master’s degree in a quantitative biomedical science field such as bioinformatics; biostatistics; quantitative epidemiology; statistical genetics; or systems biology - data science - and 2-4 years’ experience as a professional quantitative scientist.Experience equivalent to academic training may be substituted in relevant cases. Additional experience relevant to specific projects may be required.
Advanced knowledge of and post-academic experience with statistical and quantitative modeling (regression / GLM / GAM, simulation, cluster analysis, neural networks, decision trees, bagging, boosting etc.). Advanced knowledge and post academic experience with the conduct of genome wide and epigenome wide association analyses, proteomic and metabolomic analyses, and ability to apply genomic annotation to findings using UCSC browser, GTEx, ROADMAP, ENCODE or similar supporting databases.
Expert facility with more than one quantitative programming languages (R/Python/SAS/Matlab), and reasonable competence in others is required. 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 preferred.The ability to mentor students, junior colleagues, and clinical scientists in quantitative methods is desirable.
The ability to independently 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 omics research is required.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 excellent oral and/or written English language skills.