Background

The United Nations Development Programme (UNDP) is the UN’s global development network, advocating for change and connecting countries to knowledge, experience, and resources to help people build a better life. UNDP works through 136 country offices to provide development advocacy, advice, and assistance to 166 countries in Africa, Asia and the Pacific, Arab States, Eastern Europe, CIS, Latin America and the Caribbean, working to achieve the Sustainable Development Goals (SDGs).

The Strategic Plan 2022-2025 will direct UNDP’s work with countries to expand people’s choices for a fairer sustainable future, to build the world envisaged by Agenda 2030. Nowhere is this more critical than in countries experiencing crisis, conflicts and fragility, home to 76.5% of the world’s extremely poor where all aspects of Agenda 2030 are at risk.

One of the areas of responsibility of UNDP’s Crisis Bureau is to ensure that UNDP is well positioned to anticipate and to respond in the timeliest and most effective manner to crisis, primarily regarding sudden onset crises and complex protracted crises, triggered by natural disasters or armed conflicts alike. The Crisis Bureau’s Risk Anticipation Hub provides crisis risk and early warning support to HQ and to Country Offices (COs) to address their needs in contextual risk analysis, programme adaptation and early action.

To improve UNDP’s crisis risk analysis capabilities, the Crisis Bureau is exploring the targeted use of data science to harness new and emerging technologies such as machine learning / artificial intelligence and alternative data sources such as social media analytics and satellite imagery analysis, to support forecasting collective risks to human development (including risks of disasters, impact of climate change, risk of violent conflict and social unrest) in order to inform preventive action to mitigate the potential effects of crises on affected populations.

In support of UNDP’s engagement on the use of data science for crisis risk analysis and early warning, the Risk Anticipation Hub at the Crisis Bureau is seeking data science intern(s) to support the organization’s early warning capacities, information gathering and management, and the development of machine learning tools and competencies.

Duties and Responsibilities

The intern(s) will provide support to the Risk Anticipation Hub in its information management and data science tools development activities.

Advanced Analytics and Machine Learning

• Help develop statistical and machine learning models in support of multi-factor and integrated risk analysis.
• Support in designing, adapting and deploying natural language processing (NLP) applications to open-source text data (social media, news media articles, etc.).
• Assist in developing new approaches to detecting events and trends within various real-time and open-source data, such as social media, incident tracking databases, geospatial data, etc.
• Support iterative development and testing, prototyping and validating models with end-users.
• Help develop and build efficient data pipelines in cloud-based platforms and facilitate the ETL process to optimize data ingestion, cleaning, joining, merging, and automation.
• Other related duties as may be assigned.

The intern(s) will be expected to participate as an active member of the team and openly contribute his/her perspectives throughout the internship.

Competencies

Corporate: Advertisement Commitment to UNDP’s mission, vision and values Cultural, gender, religion, race, nationality and age sensitivity and adaptability Respect for the principles of the United Nations Charter and the UNDP Statement of Purpose Demonstrated interest and motivation in the field of development A desire to work with people with different language, national and cultural backgrounds Technical Skills/Competencies: Knowledge of data modeling and data mining techniques Programming in Python is essential, PySpark and R are assets Knowledge of data science / machine learning applications development and operation Knowledge of Natural Language Processing and other unstructured data are assets Knowledge of Deep Learning and Reinforcement Learning are assets Knowledge of cloud based technologies (Azure, Databricks) is an asset

Core Competencies:

Self-starter, organized, independent and reliable Able to multitask and balance multiple responsibilities Demonstrated ability to successfully interact with individuals of diverse cultural backgrounds and sensitivity to differing opinions and views

Required Skills and Experience

Education: Applicants must at the time of application, meet one of the following requirements: Be enrolled in a post graduate degree programme (Master programme or equivalent, or higher); Be enrolled in the final academic year of a first university degree programme (minimum Bachelor’s level or equivalent); Have graduated with a university degree (as defined in (a) and (b) above) and, if selected, must start the internship within one-year of graduation. Language Requirements: Advertisement Proficient in written and spoken English; Knowledge of another UN language would be an asset.