Apply for Associate Data Scientist, Geneva, Switzerland Job Vacancy | Position

Hardship Level (not relevant for home-based): H (no hardship)

Family Type (not relevant for home-based): Family

Staff Member / Affiliate Type: CONS International

Target Start Date: 2025-02-03

Deadline for Applications: December 30, 2024

Terms of Reference

As per the Terms of Reference. Recruitment of a advisor as Associate Data Scientist (AI knowledgeable – at PhD stage) for Innovation Project: Early Warning and Effective Response System. To be based mostly on the Luxembourg Institute of Science and Technology in Luxembourg.

Title of mission: Early Warning and Effective Response System (EWERS).

Purpose of mission (abstract): The mission goals to allow UNHCR and companions in nation operations to 1) enhance their capability to forecast humanitarian emergencies and the chance/impacts of displacement via nation and context-specific fashions, 2) improve knowledgeable funding planning for resilience-strengthening efforts with native communities, 3) make time-sensitive and data-informed choices to organize for and reply to emergencies via strengthened multi-stakeholder cooperation.

General Background of Project or Assignment, Operational Context: In line with the 2030 Agenda for Sustainable Development and the precept of “Leave No One Behind, ” UNHCR aspires to develop, along with strategic companions, a people-centred world Early Warning and Effective Response System (EWERS) that may systematically acquire well timed and efficient knowledge and knowledge on potential dangers and threats associated to pressured displacement brought on by battle and/or pure hazards. The EWERS will present credible and actionable data and evaluation at excessive frequency and excessive geographical decision, which might:

• allow UNHCR and companions in nation operations to enhance their capability to foretell humanitarian crises and the chance/impacts of displacement via a rustic and context particular device.
• guarantee UNHCR and the companions/stakeholders with whom UNHCR shares the alerts will have the ability to conduct knowledgeable funding planning for strengthening resiliency efforts inside native communities, in addition to make time-sensitive and data-informed choices to organize for and reply to crises via strengthened multi-stakeholder worldwide cooperation; and
• permit UNHCR and companions to harness rising applied sciences and instruments, corresponding to nowcasting, forecasting and machine learning-based fashions, for anticipatory humanitarian motion.

The mission is led by the Division of Emergency, Security and Supply, in coordination with Innovation Service and Global Data Service. The mission is carried out in coordination with the Luxembourg Institute of Science and Technology (LIST).

Purpose and Scope of Assignment: The Associate Data Scientist will report back to the Senior Project Manager and can work intently with UNHCR and LIST colleagues in addition to exterior events. S/he’ll work within the premises of the LIST and embedded within the LIST distant sensing and pure assets modelling group to work on the mission. By the tip of 2025, the mission workforce together with the Associate Data Scientist is predicted to develop a minimal viable product which offers displacement forecast over early warning system(s) for chosen pilot areas. The workforce will interact within the consumer requirement evaluation and knowledge assortment beginning January, will design and develop displacement forecast fashions beginning March, will construct a visualization platform beginning April, and can pilot and consider the system beginning September to achieve the minimal viable product objective. The Associate Data Scientist is a core member of the mission workforce and can assume following duties in coordination with UNHCR – LIST mission workforce: Research and preparation:

• Conduct analysis to research externally obtainable early warning fashions, based mostly on Uppsala University’s exterior scoping and different assets, to construct displacement fashions on.
• Conduct analysis in synthetic intelligence and discover algorithms and methodologies.
• Understand displacement dangers, potential numbers, and geographical scopes in relation to triggering occasions.
• Determine displacement triggering early warning occasions to pursue in numerous phases of the mission.
• Identify pilot international locations and focus space.
• Identify knowledge requirement and their availability.
• Identify open knowledge sources.
• Establish knowledge necessities.
• Analyze potential dangers in relation to knowledge and develop mitigation methods.

Design and improvement:

• Develop multimodal deep studying fashions to ingest multi-source knowledge, together with social media knowledge, local weather knowledge, Earth Observation (EO) knowledge, UNHCR’s registration date and so forth.
• Design multivariate time sequence based mostly early warning system by exploring fashionable deep studying fashions, corresponding to LSTM, GNN, and Transformer.
• Develop uncertainty quantification strategies to calibrate and estimate uncertainty of forecast.
• Develop (deep) causal inference/discovery algorithms to uncover causes and drivers of early warning.

Data assortment:

• Develop processes to extract, clear, and analyze datasets.
• Collect, clear, retailer, and arrange knowledge in step with UNHCR’s Data Management Guidelines.

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• Create and handle a listing in UNHCR designated cloud providers to safeguard the info collected.
• Categorize, replace, monitor and analyze knowledge.
• Create knowledge blocks to be automated and included in future purposes.

Pilot, analysis and rollout:

• Model analysis and debugging.
• Analyze and incorporate finish consumer suggestions in relation to the displacement forecasting and consumer interface software.
• Pursue deployment of the system.

Documentation:

• Document meta knowledge.
• Document sources, assets, improvement course of, outcomes (together with errors), and choices.
• Provide inputs to communication supplies, together with scientific articles.

Required {qualifications}, language(s) and work expertise: PhD in a discipline associated to machine studying, synthetic intelligence, human interplay programs, distant sensing, picture or sign processing, utilized arithmetic, pc engineering, telecommunications engineering, or pc sciences (or comparable).

Field of experience, competencies: Required/necessary:

• Experience in knowledge mining.
• Experience in creating time-series forecasting programs.
• Experience in fashionable deep studying fashions, corresponding to LSTM, GNN, and Transformer.
• Excellent programming expertise (e.g., Python, C/C++, and so forth.).
• Knowledge on pressured inhabitants displacement.
• Knowledge on database applied sciences (e.g. CouchDB, SQL)
• Solid understanding of machine studying/deep studying strategies, statistical modeling, and optimization strategies.
• Skills in presenting scientific analysis, writing papers in scientific journals, and crafting technical experiences.
• Communicative and prepared to study, self-organized, and artistic.
• Ability to work each independently and collaboratively in a global workforce.

Desirable:

• Experience in Earth Observation (EO) knowledge processing; expertise with knowledge visualization applied sciences (e.g. Tableau, RShiny, MarkdownR, MS Vision, MS InDesign/Visual Studio); familiarity with business synthetic intelligence and machine-learning software program (e.g. Watson, Crimson Hexagon, Eureqa, and so forth); expertise with cloud computing providers.

Standard Job Description: Required Languages: ,

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Desired Languages: ,

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Additional Qualifications: Skills

Education

Doctor of Philosophy (PhD) (Required)

Certifications

Work Experience

Other data: The hiring location is Geneva, Switzerland. The consultancy relies in Luxembourg. The advisor will probably be engaged on the LIST premises with the distant sensing and pure assets modeling group.This place does not require a purposeful clearance

Home-Based: No