UN Women, Data Scientist - Gender Data Lab (mis(e) À La Disposition De L'ansd), Dakar, Senegal. Dakar, Senegal Posting Date07/30/2026 BE THE FIRST TO APPLY

Organizational Context

UN Women supports the National Agency of Statistics and Demographics (ANSD) in Senegal to establish an innovative Gender Data Lab. This platform aims to centralize, analyze, and disseminate gender-specific statistics using modern visualization, analysis, and artificial intelligence tools. The Data Scientist will be seconded to ANSD to support the technical implementation of this initiative.

Job Purpose

The Data Scientist will contribute to the design and implementation of the data science and artificial intelligence components of the Gender Data Lab. This role is crucial for enhancing the production, accessibility, and utilization of gender statistics in Senegal, aligning with Sustainable Development Goal 5. The position will support ANSD in leveraging advanced data science techniques to improve public policy formulation, monitoring, and evaluation, ultimately contributing to gender equality and evidence-based decision-making.

Responsibilities

The Data Scientist will be responsible for diagnosing the Gender Data Lab's functional and technical aspects and defining priority AI use cases. Key duties include designing pipelines for preparing, transforming, and exploiting gender-specific statistical data. The role involves developing models for automated analysis and interpretation of statistics, and implementing AI components like an intelligent chatbot. This includes building and maintaining the chatbot's knowledge base, developing intelligent search mechanisms, and creating analytical indicators and decision-support tools. The Data Scientist will also evaluate model performance, document processes, collaborate with other technical experts for platform integration, and participate in pilot phases and user capacity building.

Work Experience

A minimum of two years of professional experience in data science or artificial intelligence projects is required. Experience in developing data analysis, machine learning, or AI models for statistical production is essential. Experience with open-source development or scientific publications is considered an advantage.

Skills

Proficiency in Python and data science ecosystems (Pandas, NumPy, Scikit-learn). Expertise in advanced statistical analysis, predictive modeling, Machine Learning, and Deep Learning. Mastery of generative AI techniques (LLMs, RAG, vector databases, semantic search, AI agents, NLP). Strong skills in relational and NoSQL databases, advanced SQL, ETL/ELT pipelines, and REST/GraphQL APIs. Experience with Big Data technologies (Spark, Dask) and collaborative development environments (Git).

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