Data Science Fellow (ML/NLP/LLMs) (Full-Time, Home-based)

Background

CORPORATE BACKGROUND:

UNDP works in about 170 countries and territories, helping to eradicate poverty, reduce inequalities and exclusion, and build resilience so countries can sustain progress. As the UN’s development agency, UNDP plays a critical role in helping countries achieve the Sustainable Development Goals.

The Istanbul International Center for Private Sector in Development () is the United Nations Development Programme (UNDP) global organization mandated to leverage the role of the private sector in development. The ICPSD was established in Istanbul, Turkey based on the Partnership Framework Agreement signed between the Government of the Republic of Turkey and the United Nations Development Program in March 2011. The center is one of the six global thematic policy centers of UNDP, supports the private sector and foundations to become transformative partners in development through research, advocacy, facilitation of public-private dialogue and brokering partnerships. IICPSD leads UNDP’s global work on private sector and foundations and supports UNDP’s offices all around the world.  

FELLOWSHIP OFFICE BACKGROUND:

The is a joint initiative of UNDP BPPS (Bureau for Policy and Programme Support) team, and it is hosted under UNDP ICPSD. The SDG AI Lab provides research, development, and advisory support through cutting-edge digital solutions in harnessing the potential of Artificial Intelligence (AI), Machine Learning (ML) and Geographic Information Systems (GIS) for sustainable development. The Lab aims to strengthen the UNDP’s internal and its partners’ capacities for the increasing demand for digital transformation.

The objective of the Data Science Fellowship is to provide the opportunity to work on how to deploy frontier technologies such as Artificial Intelligence (AI), Machine Learning, Deep Learning (DL), Natural Language Processing (NLP) and Large Language Models (LLMs) on development issues. In particular, the Fellow will contribute to data acquisition, data analysis, modelling, deployment, and visualizations efforts.

Duties and Responsibilities

The Fellow will assist in the following duties and responsibilities:

 

No	Duties and responsibilities	% of time
1	Research and knowledge products development Conduct research on application of Natural Language Processing (NLP) and Large Language Models (LLMs) approaches to development issues Draft analytical briefs summarizing the project findings and methodologies accessible to the public audience Conduct the data maintenance and data acquisition activities of the SDG AI Lab	30 %
2	Development and implementation of digital solutions for SDGs utilizing AI/ML/DL/NLP Develop Natural Language Processing (NLP) and Large Language Models (LLMs) solutions to tackle issues in the field of economic and international development Support the team in developing and implementing NLP and LLM solutions Manage and document the complete NLP/LLM project implementation process from conception to implementation	60 %
3	Other Provide as needed support to the Technical Specialist as required for, amongst others, participating in meetings, conferences, providing administrative support, drafting meeting minutes and performing other functions and duties Contribute to the SDG AI Lab’s Volunteer Data Scientists Initiative through advancing the volunteer engagement in SDGs related projects	10 %

Competencies

Language skills:

• Fluent in English with excellent reading and writing skills is required.
• Proficiency in French is an asset

Other competencies and attitudes:

• Interest and motivation in working in an international organization
• Good analytical skills in gathering and consolidating data and research for practical implementation
• Outgoing and initiative-taking person with a goal-oriented mind-set
• Communicates effectively when working in teams and independently
• Good in organizing and structuring various tasks and responsibilities
• Displays cultural, gender, religion, race, nationality and age sensitivity and adaptability
• Responds positively to feedback and differing points of view
• Consistently approaches work with energy and a positive, constructive attitude.

Required Skills and Experience

REQUIREMENTS AND QUALIFICATIONS

Education:

Candidates must meet one of the following educational requirements:

• currently enrolled in a postgraduate programme (such as a master’s programme or higher)
• have graduated no longer than 2 years ago from a university degree or equivalent studies

Field of study: Computer Engineering, Computer Science, Statistics, Econometrics, Mathematics, Economics  or equivalent

Completion of the Frontier Tech Leaders Machine Learning Bootcamp is an asset.

IT skills:

• Strong understanding of LLM theory, foundation models, and deep learning principles.
• Proficiency in Prompt Engineering, LLM fine-tuning, and chaining technologies like LangChain and Semantic Kernel.
• Proven expertise in project development and implementation within machine learning, using tools like Scikit-learn, TensorFlow, or PyTorch.
• Experience in executing projects related to natural language processing, utilizing NLTK, SpaCy, Bert, GPT-3, RoBERTa.
• Skilled in programming languages, particularly Python.
• Thorough knowledge of SQL and data modeling techniques.
• Hands-on experience in data science and data visualization projects using tools like Power BI or Tableau is an asset.

APPLICATION PROCEDURE:
The application should contain: 

• Brief Cover Letter (in English) stating interest in and qualifications for the post;
• Current and complete CV in English;
• Please group all your documents into one single PDF document as the system only allows to upload maximum one document.

Candidates who are selected for must submit prior to the interview the following documents: 

• Official document(s) confirming meeting at least one of the educational requirements.

Stipend 

• During the time of the fellowship, UNDP will provide a monthly stipend which will be determined for each duty station based on the stipend rates published yearly by the OHR Policy and Compensation Unit. The stipend will be paid on a monthly basis.