Sr. Research Advisor

About the role

The R&E Unit of BMIRH is seeking a Senior Research Advisor to conduct quantitative research with a focus on maternal mortality and severe maternal morbidity. Reporting to the Deputy Director, R&E Unit, this position will support the Bureau’s research agenda by identifying gaps in the scientific literature, developing high-impact research questions to reduce maternal mortality and morbidity and other adverse maternal and infant outcomes, and collaborating on the preparation of manuscripts to peer-reviewed publications.

Responsibilities

• Take required DOHMH CITI training online courses
• Receive orientation to research datasets
• Sign and submit all confidentiality forms
• Provide guidance on epidemiological research literature on health topics to appropriately frame and interpret research and data
• Affiliate in the development of research questions
• Conduct analyses and develop manuscripts in collaboration with staff
• Provide mentoring to research staff on research design, statistical methods and development of journal articles
• Other duties as assigned to support the overall goals and mission of the department/organization.

Requirements

• Ph.D. in Epidemiology, Public Health, Social Sciences, or a related quantitative field
• Senior level epidemiologist with at least 15 years of experience
• Experience as Principal Investigator on public health studies, conducting independent academic research from study design through publication
• Expertise in quantitative research methods, including causal inference (e.g. propensity score matching), machine learning techniques (e.g. random forests, decision trees, gradient boosting, principal component analysis) and advanced longitudinal analysis (e.g. mixed-effects, survival analysis)
• Experience conducting maternal mortality, severe maternal morbidity, or related maternal health research
• Proven track record of substantive publication in peer-reviewed academic journals or books
• Knowledge of health equity and structural racism and how it influences research