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About AHADI and the Role

AHADI (Applied Health Analytics for Delivery & Innovation) is dedicated to supporting public health decision-making in countries with significant disease burdens through advanced data analytics. The Analytics team at AHADI seeks a Data Scientist with strong coding and software engineering expertise to develop reliable and replicable analysis tools and databases. The team works extensively with diverse data types, including field, trial, survey, health system, climate, and environmental information, applying disease transmission and geospatial models to inform health strategies. AHADI fosters a collaborative, values-driven team environment focused on self-reliance in public health analytics in Africa.

Key Responsibilities

Develop and maintain software code to manage, visualize, and analyze various health-related datasets.
Create reproducible and automated software pipelines for data collection, management, and analysis.
Contribute to multiple AHADI projects across the analytics pipeline as required.
Select and apply suitable quantitative or software-based methods to solve analytical problems.
Promote best practices in reproducible software development within the Analytics team.
Conduct training and collaborate with partner organizations to enhance local public health analytics capabilities.
Assist in delivering training workshops and co-instructing, leveraging personal expertise.
Prepare comprehensive reports, presentations, and scientific manuscripts to communicate findings effectively to stakeholders, including ministries of health and partners.

Minimum Qualifications and Skills

Master's degree in Data Science, Statistics, Biostatistics, Epidemiology, Applied Mathematics, Computer Science, or a closely related quantitative or computational discipline.
At least 3 to 5 years of professional experience beyond the master's degree.
Expertise in statistical analysis methods, such as tests and basic regression modeling.
Proven experience developing dependable software pipelines for automated data ingestion and analysis.
Ability to create advanced dashboards and complex visualizations.
Familiarity with responsible use of AI tools for programming.
Kenyan citizenship or valid residency permit.
Willingness and ability to work from AHADI’s Nairobi office.

Preferred Qualifications

Experience handling epidemiological, public health, clinical trial, or similar health-related datasets.
Background working with survey data, routine surveillance, and raster data formats.
Skills in constructing geospatial, predictive, Bayesian, or machine learning models.

Competencies

Fluency in English and professional proficiency in at least one other language such as French, Portuguese, Arabic, or Swahili is preferred.
Strong data manipulation capabilities and expertise with at least one data analysis programming language (R or Python).
Advanced data visualization skills, including mapping techniques.
Ability to clearly communicate complex technical concepts to non-specialists.
Capability to mentor and train colleagues in data science methods.
Proven ability to manage multiple projects and methodological approaches effectively.
Willingness to occasionally work extended hours to meet deadlines.
Capacity to work both collaboratively in a team and independently with remote/distributed teams.
Preferred additional competencies include database management, AI agent development, professional software development, and deep knowledge of machine learning principles.

Additional Information and Hiring Process

Employment is contingent on successful reference checks and funding availability. Applicants must provide valid contact details for interview scheduling. Original copies of identification, academic, and professional documents will be required upon onboarding. The organization upholds equal employment opportunity policies, encouraging women and underrepresented groups to apply. Candidates with visual or hearing impairments will receive accommodations during interview and employment. Applications should include a cover letter, CV, and a GitHub code sample link sent via email. English and French support for application documents and interviews is available.

Data Scientist