Senior Statistician – Disease Burden Analysis job at Infectious Diseases Institute

About the Organization

The Infectious Diseases Institute (IDI) is a Ugandan not-for-profit organization whose mission is to strengthen health systems in Africa, with strong emphasis on infectious diseases, through research and capacity development. IDI has six operational areas through which it works to achieve its mission: Prevention, Care and Treatment; Training, Research, Laboratory services (including the CAP-certified IDI Core Lab & Translational Lab), Global Health Security and Health System Strengthening.

Job Description

The Infectious Diseases Institute is seeking a highly skilled and experienced Senior Statistician to lead the analysis and synthesis of disease burden data in Uganda and in other African Countries. The successful candidate will be responsible for processing, cleaning, and analyzing secondary datasets collected from various sources, including disease programs, DHIS2, and National and international data repositories. The primary objective of this role is to contribute to the analysis of the current disease burden and generate evidence advocacy, health programming, and planning in Africa.

Duties and Responsibilities

Clean and preprocess large-scale secondary datasets from diverse sources, ensuring data quality and integrity.
Conduct advanced statistical analyses to quantify disease burden, trends, and projections across multiple countries in Africa.
Collaborate with internal and external stakeholders to define research questions, statistical methodologies, and analytical approaches.
Produce high-quality reports, presentations, and visualizations summarizing key findings for diverse audiences, including scientific communities, donor agencies, and policymakers.
Communicate complex statistical concepts and results effectively to non-technical stakeholders, facilitating informed decision-making.
Work closely with project teams (epidemiologists, and modelers) and collaborators to ensure alignment with project timelines, objectives, and deliverables.
Provide technical guidance and mentorship to junior staff members involved in data analysis and interpretation.
Engage the already established technical working groups and the donor to ensure that the employed methodologies and results from analyses make scientific and policy sense.
Stay abreast of advancements in statistical methods, epidemiology, and public health research, integrating new methodologies into analyses as appropriate.
Contribute to the development of research proposals, study protocols, and grant applications as needed.

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Qualification, Experiences and Competencies

Master’s or Ph.D. degree in Statistics, Biostatistics, Epidemiology, Public Health, or a related field.
Proven experience (minimum 5 years) in processing, analyzing, and interpreting complex datasets, preferably in the context of public health or epidemiological research.
Proven track record of producing high-quality research outputs, including peer-reviewed publications and technical reports.
Experience working collaboratively in multidisciplinary teams and managing relationships with external partners and stakeholders.
Strong organizational skills and ability to manage multiple tasks simultaneously in a fast-paced environment.
Fluency in English is required, proficiency in additional languages commonly spoken in Africa (French) is desirable.
Demonstrated leadership skills and ability to work independently with minimal supervision.

Required Skills:

Expertise in statistical software packages (e.g., Python, R, Stata) and data management tools for handling large datasets. Experience in more than one programming language is an added advantage. IDI currently does not provide access to SAS.
Skills in data management and database querying are important for handling large healthcare datasets efficiently, ensuring data quality, and maintaining data integrity.
Demonstrated ability to apply advanced statistical methods, such as multivariate regression, survival analysis, time series analysis, and Bayesian modeling.
Strong understanding of epidemiological study designs, sampling techniques, and data collection methods.
Excellent written and verbal communication skills, with the ability to convey technical information clearly and concisely to diverse audiences.
Familiarity with health information systems, including DHIS2 and other national data platforms.
Data visualization skills.