Statistician

Intellectual Ventures Management - Bellevue, WA3.6

Full-timeEstimated: $72,000 - $94,000 a year
EducationSkills
Job Description

The Institute for Disease Modeling shapes global efforts to eradicate infectious diseases and to achieve permanent improvements in the health of those most in need. By developing, using, and freely sharing computational modeling tools, we advise policymakers, promote quantitative decision-making and advance scientific methodologies. IDM is a highly dynamic organization, composed of research scientists and software professionals, with a work environment that is defined by innovation and collaboration. As part of our work, we routinely collaborate with groups at the World Health Organization, the Center for Disease Control, PATH, the Bill and Melinda Gates Foundation, ministries of health in the developing world, as well as universities and research institutes. IDM is an institute within the Global Good Fund, a collaboration between Intellectual Ventures and Bill and Melinda Gates.

We seek a full-time Statistician to identify and lead or support research projects relevant to different aspects of the group’s analysis and modeling work (e.g. Polio, vaccine preventable diseases, health delivery), as well as to actively partner/support with other teams at IDM (e.g. MNCH, Health Economics, Measles, Epidemiology, Malaria, HIV/TB). Joining our group provides unique opportunities to interact with global health policy makers, to collaborate with world-class research laboratories and non-profit organizations, and to contribute to global and national disease eradication strategies.

The statistician will focus on diverse data and problems related to disease modeling and control strategies, analysis of risk factors, risk mapping, study design, and diagnosis/optimization of global health programs and delivery systems. In collaborations with team members, external researchers, policymakers, and/or country health programs, the statistician may lead on solutions, support with analysis, or contribute subject-matter expertise on sound inferential practices and methods. The scientist will present to key stakeholders, at conferences, and prepare research articles.

Our group seeks individuals with demonstrated achievements, a commitment to excellence, and a willingness to collaborate.

Responsibilities:
Flexibly engage in diverse policy and analysis questions that arise related disease control efforts and healthcare delivery
Provide subject matter expertise to internal team members and external collaborators on statistical methods and practice, e.g. sampling, model building, estimation, and interpretation
Support polio eradication efforts with analysis on risk and assessment of interventions
Gather, analyze, and model data about health gaps/burden, health interventions, and health delivery in countries of interest, e.g. maternal and child health
Write summaries of results to be used in policy recommendations, white papers, and scientific publications
Write research articles and conference presentations communicating projects and results to the scientific community

Key Qualifications and Required Skills:
PhD in Statistics, Biostatistics, or equivalent
Extensive knowledge of diverse statistical methods and application to data (applied statistics)
Proficiency in at least one data-analysis or scripting language (e.g. R, Python)
Knowledge of experimental design and sampling principles
Experience with various estimation paradigms/techniques, e.g. likelihood inference, Bayesian statistics
Ability to initiate, organize, and manage research projects and clearly communicate analysis results to diverse audiences
Demonstrated ability to work productively independently and as part of a team; work extended hours to meet a deadline
Knowledge of public health issues in developing world settings
Experience working with a software development team is a plus
Multiple peer-reviewed scientific articles

Desired Skills:
Familiarity with survey statistics, design-based inference
Experience with aspects of spatial statistics, disease mapping, and GIS
Knowledge of machine learning/statistical learning concepts and applications
We are an equal opportunity employer