Senior Coordinator, Data Scientist at eHealth Systems Africa

Purpose of the position

• We are looking for a Senior Data Scientist with the skills, experience, and mindset to drive innovation in applied analytics, modeling, and decision intelligence. The ideal candidate is expected to build and implement real-world data use cases in areas such as health campaigns, demographic forecasting, climate risk modeling, and food security assessment. You will be responsible for driving high-impact analytical projects across multiple domains, developing models and insights that support both operational and strategic goals.

Keywords: Data, Engineering, Analytics, Sprint Planning, Capacity building, ODK

What you’ll do

• To perform this job successfully, an individual must be able to perform each essential duty satisfactorily. Other duties may be assigned:

Data Management

• Conduct spatial analysis and develop geospatial models to identify patterns, trends, and relationships within the data.
• Oversee data collection, storage, and retrieval processes to ensure accuracy, security, and availability.
• Develop and enforce data management policies, procedures, and standards.
• Manage data governance initiatives to ensure compliance with legal and regulatory requirements.
• Develop dashboards, reports, and data visualizations to present insights to stakeholders.
• Perform data mining, statistical analysis, and predictive modeling to address complex business questions.
• Collaborate with cross-functional teams to identify data-driven opportunities for improvement.

Data Engineering and Integration

• Work closely with data engineers to improve data pipelines, data quality, and feature engineering.
• Assist in the development of robust data architectures and MLOps pipelines.
• Implement data quality frameworks to monitor and enhance the reliability of datasets.

Domain-Specific Modeling Use Cases

• Senior Coordinator, Data Scientist: Develop models to identify underserved populations, forecast disease spread, and support vaccine or intervention microplanning.
• Demography: Build spatial demographic models using satellite imagery, census microdata, and administrative boundaries for population forecasting and resource targeting.
• Climate Analytics: Analyze weather, hydrological, and satellite-derived datasets (e.g., ERA5, CHIRPS, WRF output) to model environmental risks such as heatwaves, flooding, and droughts.
• Food Security: Integrate crop indices, remote sensing, market data, and socio-economic indicators to predict food insecurity trends and design resilience strategies.

Team Collaboration and Leadership

• Lead and mentor a team of data analysts and engineers, fostering a collaborative and innovative work environment
• Mentor junior data scientists and analysts, providing code reviews and guidance on best practices.
• Lead internal knowledge-sharing sessions and stay current with industry trends and tools

Who you are

The requirements listed below are representative of the knowledge, skill, and/or ability required to successfully perform this job.

• Master’s or PhD in , Statistics, Applied Mathematics, Data Science, Public Health, demography, GIS or a related field.
• Minimum of proven seven (7) years of experience in data science or applied analytics roles.
• Strong knowledge of machine learning frameworks (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch).
• Proficiency in Python and/or R for statistical modeling and analysis.
• Experience with cloud platforms (e.g., AWS, Azure, or GCP) and big data tools (e.g., Hadoop, Spark) including model deployment (e.g., SageMaker, Vertex AI)
• Strong understanding of data modeling, databricks, ETL processes, (Apache Spark or PySpark, Apache Beam, dbt (Data Build Tool),Ruffus / Bonobo / Luigi)
• Experience with demographic data sources (e.g., DHS, WorldPop, HRSL, GHS-POP) and climate datasets (ERA5, CHIRPS, MODIS, NASA POWER).
• Exposure to humanitarian or development contexts (e.g., WHO, UN, NGOs, or government agencies) is highly desirable.
• Domain experience in [e.g., public health, geospatial, research].
• Working knowledge of geospatial analytics or unstructured data (e.g., images, text).
• Experience with A/B testing, causal inference, or time-series forecasting.

Certifications and Licenses

• Data Science Certification
• PMI Agile Certified Practitioner (PMI-ACP), AgilePgM- Optional
• Certification in cloud services (e.g., AWS Certified Data Analytics, Azure Data Engineer Associate).
• Familiarity with big data platforms and real-time streaming.