ASSOCIATE DATA SCIENTIST

Organizational Context

The Independent Institution on Missing Persons in the Syrian Arab Republic (IIMP) was established by the UN General Assembly in June 2023. This role, currently based in Geneva, may be subject to relocation to Damascus or other operational locations. The incumbent reports to a Human Rights Officer.

Job Purpose

The Associate Data Scientist will support programmatic areas, particularly concerning missing persons in Syria, by applying data science methods to clarify their fate and whereabouts. This involves exploring and acquiring data, cleaning and standardizing it, and developing data science products using advanced analytical methods like AI and machine learning. The role contributes to uncovering insights from large datasets, analyzing patterns, and communicating findings through visualizations and reports. The incumbent will also guide and train general service staff in data science functions.

Responsibilities

Assists in identifying and acquiring diverse data sources for analytical use. Applies quality methods to structure, clean, and standardize data. Utilizes data science methods to support programmatic areas, specifically contributing to efforts to clarify the fate and whereabouts of missing persons in Syria. Designs and develops data science products using AI, machine learning, and other advanced analytical techniques to reveal insights. Analyzes large datasets to identify patterns and relationships, developing analytical outputs and visualizations for communication. Guides and supervises general service staff in data science functions.

Work Experience

A minimum of two years of progressive experience in data science, data analytics, or a related field is required. Desirable experience includes proficiency with data science programming tools (e.g., Python, R), data manipulation and visualization tools (e.g., pandas, Power BI), natural language processing, document review platforms, databases (SQL/NoSQL), and analyzing data related to Syria.

Skills

Proficiency in the data analysis lifecycle, statistical and computational methods (e.g., machine learning, regression), and data visualization. Strong teamwork and collaboration skills. Technological awareness and ability to apply technology to tasks. Professionalism, conscientiousness, and ability to work under pressure.

Explore related opportunities