Statistician, Malaria and Neglected Tropical Diseases

PATH | Seattle, WA

Posted Date 3/18/2021

*Please include a cover letter with your resume describing your interest in the position and how you meet the qualifications.

PATH is a global organization that works to accelerate health equity by bringing together public institutions, businesses, social enterprises, and investors to solve the world’s most pressing health challenges. With expertise in science, health, economics, technology, advocacy, and dozens of other specialties, PATH develops and scales solutions—including vaccines, drugs, devices, diagnostics, and innovative approaches to strengthening health systems worldwide.

PATH has unparalleled expertise and experience in the development of new tools and strategies for malaria elimination and has the potential to become an acknowledged leader in accelerating efforts towards malaria elimination and global eradication.

The Malaria and Neglected Tropical Diseases program, as a leader in the effort to end malaria illnesses and deaths, refines and develops tools and approaches, supports national programs, and builds evidence and data to empower national governments to pursue malaria elimination.

PATH’s Malaria Portfolio is seeking a full-time statistician with strong experience in experimental and quasi-experimental study design and statistical analysis.


Experience in statistical approaches to experimental and quasi-experimental program evaluation, including interrupted time series analysis, preferably for malaria, who would be able to:

  • Provide technical guidance and in some cases lead the statistical analysis of malaria intervention and outcomes data
  • Provide technical guidance in the design of planned studies involving experimental or quasi-experimental analytical approaches, including interrupted time series and analysis of cluster randomized trials
  • Provide guidance in techniques to address challenges with datasets, such as multiple imputation for missing data, addressing data incompleteness
  • Advise team members in the choice of statistical packages, review code and recommend diagnostics based on the model
  • Run simulation analyses to determine power/sample size and other parameters of interest
  • Review analysis results and support the interpretation and writing of results for peer-reviewed publications
  • Supervise and mentor junior technical staff members
Listing Type
Position Type
Full Time
Employer Type
Direct Employer

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