Associate Data Analyst

Key Responsibilities

Data Management & Quality Assurance

 

• Collect, clean, validate, and organise public health survey and programme data from multiple sources, ensuring accuracy and consistency.
• Maintain structured datasets and documentation in line with industry standards.
  
   

Statistical & Epidemiological Analysis

 

• Conduct descriptive and inferential statistical analysis on health outcomes, user engagement, and programme indicators.
• Apply epidemiological methods to identify trends, patterns, and risk factors within Sproxil’s user and health data.
• Support development and tracking of key performance indicators against established benchmarks.
  
   

Programme Monitoring & Evaluation

 

• Support monitoring and evaluation (M&E) frameworks for Sproxil and related grant-funded health programmes.
• Contribute to donor and stakeholder reporting by providing accurate, well-contextualised
  
   

data summaries.

 

• Assist in designing data collection tools and indicators for new programme initiatives.
  
   

Reporting & Visualization

 

• Build dashboards, charts, and reports that translate complex data into actionable insights for leadership.
• Prepare periodic analytical reports highlighting trends, anomalies, and recommendations.
  
   

Cross-Functional Collaboration

 

• Work closely with the Product, Technology, and Grants teams to align data analysis with organisational and programme goals.
• Support ad-hoc data requests and analyses for leadership and external partners as needed.
  
   

Requirements

Qualifications & Requirements

Education

 

• Bachelor's degree in Epidemiology, Biostatistics, Public Health, Global Health, Statistics, or a related quantitative field. A Master's degree is an advantage.
  
   

Experience

 

• 1–3 years of experience in data analysis, epidemiology, biostatistics, monitoring & evaluation, or global health programme evaluation.
• Prior exposure to donor-funded, public health, or research programmes is strongly preferred.
• Experience working with health data systems or large datasets in a research, NGO, or public health setting.
  
   

Technical Skills

 

• Proficiency in statistical software such as R, Stata, or SPSS, alongside strong Excel skills.
• Familiarity with data visualisation tools (Power BI, Tableau, or similar).
• Experience with data collection platforms such as DHIS2, REDCap, KoBoToolbox, or ODK is an advantage.
• Understanding of M&E frameworks, logical frameworks (logframes), and standard health/programme indicators.
  
   

Core Competencies & Soft Skills

 

• Strong analytical thinking and attention to detail when working with health and programme data.
• Ability to communicate technical findings clearly to non-technical stakeholders.
• High level of integrity and discretion in handling sensitive health data.
• Self-motivated, organised, and comfortable managing multiple data requests and deadlines.
  
   

Benefits

What We Offer

 

• Competitive compensation aligned with experience and qualifications.
• The opportunity to apply public health and statistical expertise within a fast-growing AI-native organisation.
• Flexible hybrid work arrangement.
• Exposure to cross-functional work spanning technology, product, and grants-funded health programmes.
• A mission-driven team committed to expanding access to quality healthcare through data and technology.