DATA SCIENTIST

Organizational Context

The Policy, Evaluation and Training Division (DPET) within the UN Secretariat's Department of Peace Operations (DPO) develops policy, doctrine, and training for peacekeeping operations. The Policy and Best Practices Service (PBPS) specifically supports DPO and DOS by fostering best practices and providing policy guidance. This Data Scientist role is situated within PBPS in New York, reporting to the Senior Programme Management Officer.

Job Purpose

The Data Scientist's primary purpose is to support peacekeeping operations by monitoring, analyzing, and responding to mis/dis/malinformation and hate speech. This involves leveraging data to identify trends, patterns, and insights that can inform strategies and improve operational effectiveness. The role contributes to enhancing programme development, advocacy, and business strategies through data-driven decision-making. Additionally, the Data Scientist will develop technology solutions for analyzing the digital information environment and utilize predictive modeling to optimize outcomes, ensuring data integrity and compliance with UN standards throughout the process.

Responsibilities

Analyze large, complex datasets to extract insights using appropriate techniques and platforms. Prepare reports communicating trends and patterns with relevant data and visualizations. Ensure data integrity and compliance with privacy regulations and UN best practices. Collaborate with stakeholders to identify data-driven business solutions, liaising with technology providers, civil society, international organizations, and Member States. Mine and analyze organizational databases to optimize programme development, advocacy, and business strategies. Assess the effectiveness and accuracy of new data sources and gathering techniques. Develop technology solutions for monitoring and analyzing the digital information environment. Employ predictive modeling to enhance entity experiences and business outcomes. Develop and implement A/B testing frameworks to evaluate model quality. Coordinate with functional teams for model implementation and outcome monitoring. Establish processes and tools for monitoring model performance and data accuracy.

Work Experience

A minimum of five years of experience in data science, data analytics, applied mathematics, or information management is required. Experience developing technology solutions for analyzing digital and analogue information environments is also required. Experience with data science tools (e.g., Jupyter, R, Python) and using data to inform strategies is desirable.

Skills

Data analysis life cycle (ingest, wrangling, analysis, visualization), developing digital software tools, statistical and computational methods (clustering, classification, machine learning, regression), data-driven decision-making, judgment, planning, organization, teamwork, and communication.

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