Functioning under the direction of the principal investigators and other faculty members, the Research Specialist works independently to help design and analyze high level, complex research studies using Machine-Learning, Deep Learning methods, and other relevant statistical solutions. The Research Specialist contributes to the critical evaluation of the scientific literature, writing of scientific reports and manuscripts (including co-authorship as appropriate), development of presentations, and preparation of research grant proposals. The Research Specialist works in a close-knit, internationally known research unit of 25 Harvard faculty and 60 support staff.
PRINCIPLE DUTIES INCLUDE:
Under the direction of principal investigators, assists in the design, planning, and execution of analyses comparing therapeutics in claims data and electronic health records (EHR) using commonly used statistical models with a focus on Machine-Learning and Deep Learning methods. As a core member of the research team, helps to analyze data and interpret findings; prepares summaries, reports, manuscripts and presentations based on study results. Contributes to the dissemination of scientific evidence through oral and poster presentations and published manuscripts.
Specific duties include:
Performs advanced data analysis with a focus on Machine-Learning and Deep Learning methods
Contributes to interpretation of research data and results
Conducts literature reviews to help refine the study question and inform the study design
Participates in study design and protocol development
Contributes to writing of research reports
Contributes to development of manuscripts, oral and poster presentations for evidence dissemination
Participates in research grant proposal preparation
Participates in Institutional Review Board (IRB) submission process for new research protocols
MS or equivalent degree in Data Science, Bioinformatics, Biostatistics, Epidemiology, or related fields
Excellent knowledge of and experience with Machine-Learning/Deep Learning and epidemiologic methods
Strong programming skills, preferably in R and/or Python, are required.
Experience in research using large claims databases or electronic health records is an advantage but not necessary
SKILLS/ ABILITIES/ COMPETENCIES REQUIRED:
The successful candidate will have very good theoretical and applied knowledge of biostatistics or bioinformatics to help implement advanced statistical analyses. The candidate must have strong programming skills to implement commonly used Machine-Learning and Deep Learning models using R, Python, or other statistical packages. Strong time management/organizational skills as well as written and verbal presentational skills are expected.
Professional Office Environment, Business Casual. Working in a close-knit, friendly and helpful & internationally known research unit of 20+ Harvard faculty and 40 support staff.
SUPERVISORY RESPONSIBILITY: None
FISCAL RESPONSIBILITY: None
HOSPITAL WIDE RESPONSIBILITIES:
Works within legal, regulatory, accreditation and ethical practice standards relevant to the position and as established by BWH/Partners; follows safe practices required for the position; complies with appropriate BWH and Partners policies and procedures; fulfills any training required by BWH and/or Partners, as appropriate; brings potential matters of non-compliance to the attention of the supervisor or other appropriate hospital staff.
Brigham and Women's Hospital (BWH) complies with applicable Federal civil rights laws and does not discriminate on the basis of race, color, national origin, citizenship, alienage, religion, creed, sex, sexual orientation, gender identity, age, or disability. BWH does not exclude people or treat them differently because of race, color, national origin, citizenship, alienage, religion, creed, sex, sexual orientation, gender identity, age, or disability