Top level Organizer, Data engineer at eHealth Systems Africa in Abuja

Objective of the role

We are seeking a Top level Data engineer with the competencies, expertise, and mentality to foster creativity in submitted application data analysis, modeling, and decision intelligence. The preferred candidate is anticipated to build and execute real-world data application scenarios in zones which includes health marketing, demographic predicting, climate risk modeling, and food guard evaluation. You will be in charge of pushing high-effect logical projects across various domains, conceptualizing models and findings that assist both business and strategic targets.

What you’ll do

To execute this position successfully, an individual must be capable to execute each necessary function okay. Other obligations may be allocated:

Data governance:

• Carry out spatial evaluation and formulate geospatial models to recognize patterns, practices, and connections inside the data.
• Supervise data collection, storage, and retrieval methods to guarantee precision, guard, and accessibility.
• Formulate and ensure adherence to data governance rules, standardized processes, and guidelines.
• Oversee data administration programs to guarantee adherence with legal & regulatory qualifications.
• Formulate dashboards, documentation, and data visualizations to show findings to participants.
• Execute data mining, statistical evaluation, and predictive modeling to handle sophisticated business questions.
• Work alongside cross-operational teams to recognize analytics-based avenues for advancement.

Who you are

• Master’s or PhD in , Statistics, Submitted application Mathematics, Data Science, Community health, demography, Geographic information system or a relevant field.
• At least proven seven (7) years of expertise in data science or submitted application data analysis positions.
• Solid understanding of machine learning frameworks (e.g., Scikit-learn, XGBoost, TensorFlow, PyTorch).
• Competence in Python and/or R for statistical modeling and evaluation.
• Expertise with cloud channels (e.g., AWS, Azure, or GCP) and big data resources (e.g., Hadoop, Spark) which includes model deploying (e.g., SageMaker, Vertex AI)
• Deep knowledge of data modeling, databricks, ETL methods, (Apache Spark or PySpark, Apache Beam, dbt (Data Build Instrument),Ruffus / Bonobo / Luigi)
• Expertise with demographic data suppliers (e.g., DHS, WorldPop, HRSL, GHS-POP) and climate data collections (ERA5, CHIRPS, MODIS, NASA POWER).
• Exposure to humanitarian or development situations (e.g., WHO, UN, Nonprofit organizations, or regulatory bodies) is highly preferred.
• Domain expertise in [e.g., community health, geospatial, analysis].
• Practical understanding of geospatial data analysis or unstructured data (e.g., images, text).
• Expertise with A/B running test, causal inference, or time-series predicting.

Qualifications and Permits:

• Data Science Accreditation
• PMI Nimble Accredited Practitioner (PMI-ACP), AgilePgM- Optional
• Accreditation in cloud solutions (e.g., AWS Accredited Business intelligence, Azure Data scientist Associate).
• Understanding with big data channels and instantaneous streaming.