Senior Data Scientist (P-5)
 
 Organization: United Nations Environment Programme (UNEP)
 Location: Nairobi, Kenya (Chief Digital Office)
 Application Deadline: 21 February
 
 Role Overview

  •  Leads the Applications, AI and Data Science function within UNEP’s Chief Digital Office.
  •  Oversees UNEP’s data platforms and applications across corporate and programmatic areas.
  •  Drives UNEP’s Digital Transformation agenda, supporting evidence-based environmental decision-making to tackle climate change, nature loss, and pollution.
  •  Advises senior management on emerging trends in data science and digital innovation.

 
 Key Responsibilities

  •  Provide strategic, technical, and managerial leadership of the data science program and team.
  •  Identify, acquire, and structure high-quality internal and external data sources for decision support.
  •  Lead the design and deployment of advanced analytics solutions, including AI, machine learning, predictive analytics, NLP, data mining, and Generative AI.
  •  Oversee development of production-grade data platforms and applications.
  •  Translate business needs into technical roadmaps in collaboration with business analysis teams.
  •  Develop visualization and reporting products suitable for senior leadership, oversight bodies, and external stakeholders.
  •  Represent UNEP at international, regional, and inter-agency meetings.
  •  Guide, train, and supervise staff within the Applications, AI, and Data Science function.

 
 Requirements

  •  Advanced degree (Master’s or equivalent) in data science, mathematics, statistics, engineering, or a related field; environmental applications focus desirable.
  •  Minimum 10 years of progressively responsible experience in data science, analytics, applied mathematics, or software engineering.
  •  Experience with statistical and computational methods (clustering, classification, correlation, dimension reduction, forecasting, machine/deep learning, Generative AI).
  •  Proficiency in data science tools and programming languages (Python, R, Jupyter, Matlab, Knime, SPSS, SAS, Hadoop, Spark, etc.).
  •  Experience managing software development and data science teams delivering production-grade applications.
  •  Experience in international or environmental contexts desirable. 

 
 Applicaton link- %contact_placeholder% (21/02)