careers

Data Unit Manager

AfriGIS seeks a dynamic and results-driven Data Unit Manager to join our team.

Qualifications & Experience:

  • Bachelor’s degree (Master’s preferred) in Computer Science, Data Science or a related field.
  • 8+ years of experience in data management, data science or a similar role, with at least 3 years in a leadership capacity.
  • Background in AI model development, machine learning, and predictive analytics.
  • Proficiency in programming languages (Python, R, SQL) for data processing and automation.
  • Extensive experience in data cleaning and data mining principles.
  • Strong background in data analysis, visualisation, and predictive modelling.
  • Excellent communication skills, with the ability to present complex spatial data to non-technical stakeholders.

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Intermediate Database Administrator (DBA), Contract Position

AfriGIS seeks a dynamic and results-driven Database Administrator to join our team.

Qualifications & Experience:

  • Relevant tertiary qualification in Computer Science, Information Systems, or a related field.
  • 3 - 5 years of experience administering Microsoft SQL Server and/or PostgreSQL.
  • Certification in Microsoft SQL Server (e.g., MCSA/MCSE) or PostgreSQL (e.g., EDB PostgreSQL Associate).
  • Strong working knowledge of:
    •  T-SQL and/or PL/pgSQL.
    • Expertise in backup/restore strategies and disaster recovery planning.
    • Proficiency with query performance analysis tools.

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Data Specialist

AfriGIS seeks a dynamic and results-driven Data Specialist to join our team.

Qualifications & Experience:

  • Bachelor’s degree (Master’s preferred) in Geoinformatics, Geospatial Science, Computer Science, or a related field.
  • 8+ years of experience in GIS, spatial data management, or a similar role
  • Extensive experience with one or more GIS software tools (QGIS, MapInfo, ArcGIS) and spatial databases (PostGIS, SQL Server and Oracle).
  • Deep knowledge of datasets, such as deeds and cadastre.
  • Proficiency in SQL for spatial data processing and automation.
  • Experience in machine learning and AI applications in geospatial analytics.
  • Strong background in geospatial data analysis, visualisation, and predictive modelling.
  • Geological classification map styling knowledge to ensure correct data visualisation.

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