Data Scientist II

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. 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. Participants in education and peer mentoring of clinical colleagues. 

Requires familiarity and experience with statistical analysis, software development, visualization, algorithm development, supervised and unsupervised learning, predictive analytics, and expert skills in at least some of these specialized areas. Advanced skills in data management, manipulation, and summarization are critical, and skills in natural language processing are a plus. Strong written and oral communication skills are essential, as is the ability to lead and independently develop quantitative analysis. Must be able to fully and independently develop quantitative analytic schema, carry it through to completion, and develop documentation and reporting of same. Expert use of rigorous version control and the principles of reproducible research are required. The ability to work in a team-based research environment is essential. The ability to supervise junior colleagues or students in entry-level roles is a plus. 

Responsibilities:
Provide data management, manipulation, cleaning, and analysis support for biomedical research projects, and serve as representative of the data science function on small to intermediate scale projects. Independently or as a team member develop algorithms and software tools facilitating scientific productivity, project completion, and the reproducible research environment, and present technical aspects of development to specialized and general audiences. Generate analysis pipelines and automated functions for repetitive summaries and analyses. Maintain coding libraries and team resources consistent with advanced standards. 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. Present work to internal and external parties. Prepare tabular, graphical, and narrative summaries of findings of publication quality. Participate in the development of funding applications driving future work. 

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 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.). Expert facility with more than one quantitative programming languages (R/Python/SAS/Matlab), and reasonable competence in others is required. Experience with database technologies (SQL, REDCap) is essential. 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 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 excellent oral and/or written English language skills.