Data Science Analyst – national position at UNDP – Istanbul, Türkiye

Diversity, equality and inclusion are core principles at UNDP: we value diversity as an expression of the multitude of countries and cultures in which we operate, we promote inclusion as a way to ensure that all staff are empowered to contribute our mission, and we ensure equality and fairness in all our actions. Taking a “leave no one behind” approach to our diversity efforts means increasing representation of underserved populations. People who identify as belonging to a marginalized or excluded population are strongly encouraged to apply. Learn more about working at UNDP, including our values ​​and inspiring stories.

UNDP will not tolerate sexual exploitation and abuse, harassment of any kind, including sexual harassment, or discrimination. All selected candidates will therefore undergo strict reference and background checks.

The Istanbul International Center for Private Sector in Development (ICPSD) of the United Nations Development Program (UNDP) has a mandate to strengthen the role of the private sector in development. The ICPSD was established in Istanbul, Türkiye, based on the Partnership Framework Agreement signed in March 2011 between the Government of the Republic of Türkiye and the United Nations Development Programme. The Center is one of UNDP’s six global thematic centres, advocating and facilitating the private sector’s contribution to human development and inclusive growth.

The ICPSD SDG AI Lab is a joint initiative of the UNDP BPPS (Bureau for Policy and Program Support) team and is hosted under UNDP ICPSD. The SDG AI Lab provides research, development and advisory support through innovative 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 internal capabilities of UNDP and its partners for the increasing demands for digital transformation.

UNDP ICPSD’s SDG AI Lab and UN Technology Bank are jointly implementing the ‘Frontier Tech Leaders’ Program (FTL) for Least Developed Countries (LDCs) to bridge the digital divide and contribute to the 2030 Agenda for Sustainable Development. The ‘Frontier Tech Leaders’ program aims to train the next generation of technology specialists in the least developed countries (LDCs) to address the challenges facing their communities by developing digital solutions. In this sense, it will inspire the youth and provide them with the tools to take action. With a focus on encouraging young women to pursue education and careers in technology fields, the program will help promote gender equality.

The initiative is planned to be implemented in the least developed countries (LDCs), involving young technology specialists. The first cohort began in August 2023. Participants will benefit from the Machine Learning Bootcamp, involvement in local chapter activities, and participation in the Virtual Digital Business Incubation Program, while also becoming integral members of the global community of technology leaders. This program empowers young talents to co-create solutions for the Sustainable Development Goals (SDGs) and focuses on developing their technical and soft skills, preparing them to emerge as Frontier Tech Leaders.

The Data Science Analyst will be responsible for the Frontier Tech Leaders Program Training component and support overall program implementation. The analyst will also contribute to the development of digital solutions for SDGs.

Tasks and responsibilities

Under the direct supervision and general direction of the technical specialist, the Data Science Analyst has the following responsibilities:

Overseeing the FTL training component:

• Develop content for FTL Training Component.
• Preparing and continuously improving the FTL training program.
• Support country implementation course guides and volunteer trainers.
• Teach and assist students with Machine Learning, Python and other technical sessions.
• Arrange learning sessions and office hours schedule.
• Create a positive, organized learning atmosphere.

Development and implementation of digital solutions for SDGs:

• Develop ML and DL models by applying supervised and unsupervised techniques to structured and unstructured Big Data.
• Build and deploy AI/ML/DL models using the relevant techniques.
• Design and implement data quality procedures to support data quality management activities for data pipelines.
• Research and experiment with custom software using the relevant techniques for the data such as Machine Learning.
• Development and technical review of knowledge products.

Facilitating knowledge and capacity building and knowledge sharing.

• Identify, synthesize and document best practices and lessons learned emerging from the project and implementing partners.
• Promote advocacy on development trends and opportunities to collaborate in coordination with UNDP program partners, stakeholders and communications staff.

The incumbent shall, within his or her functional profile, perform other duties deemed necessary for the efficient functioning of the Office and the Organization

Institutional arrangement

The Data Science Analyst will work under the direction of and report directly to the UNDP ICPSD Technical Specialist.

Competencies

Core competencies:

• Achieving results: LEVEL 1: Plans and monitors own work, pays attention to details, delivers quality work within deadline
• Think innovatively: LEVEL 1: Open to creative ideas/known risks, is a pragmatic problem solver, makes improvements
• Continuous learning: LEVEL 1: Open and curious, shares knowledge, learns from mistakes, asks for feedback
• Adapt with flexibility: LEVEL 1: Adapts to change, deals constructively with ambiguity/uncertainty, is flexible
• Act with determination: LEVEL 1: Demonstrates drive and motivation, able to perform calmly in the face of adversity, confident
• Involve and partner: LEVEL 1: Shows compassion/understanding for others, forms positive relationships
• Enabling diversity and inclusion: LEVEL 1: Value/respect differences, aware of unconscious biases, confront discrimination

Cross-functional and technical competencies:

• Data Collection: Be skilled in data sorting, data cleaning, managing studies, presenting and reporting, including collecting real-time data (e.g. mobile data, satellite data, sensor data).
• Data engineering: Proficiency in programming languages ​​such as SQL, Python and R, being adept at finding warehousing solutions and using ETL (Extract, Transfer, Load) tools, and understanding basic machine learning and algorithms.
• Data Analytics: Ability to extract, analyze and visualize data (including real-time data) to form meaningful insights and support effective decision making.
• Machine learning: Skilled in computer algorithms that automatically improve through experience and the use of data.
• Data governance: Knowledge of data science, skills to develop data management tools, organize and maintain databases and use data visualization technologies.
• Data storytelling and communication: Skilled at building a story around a set of data and its associated visualizations to convey the meaning of that data in a powerful and compelling way.
• Digital awareness and literacy: Ability and inclination to quickly adopt new technologies, either by skillfully understanding their use or by understanding their impact and enabling others to use them as needed.

Required skills and experience

Education:

A university degree (master’s degree or equivalent) in computer engineering, computer science, statistics, mathematics, engineering or other related field is required. OR

A first-level university degree (bachelor’s degree) combined with two years of additional qualifying experience will be considered in lieu of the advanced university diploma.

Experience:

• Applicants with a master’s degree (or equivalent) in a relevant field of study are not required to have professional work experience. Applicants with a bachelor’s degree (or equivalent) must have a minimum of two (2) years of relevant professional experience in data science, data analytics, data engineering, machine learning or other related fields.

• Proven and demonstrated knowledge or experience in developing and implementing projects in the field of Artificial Intelligence and Machine Learning is required.
• Strong programming skills, preferably with Python, are required.
• Demonstrated experience in implementing digital capacity/skills building projects is a clear advantage.
• Experience delivering remote skills training, e-learning and online learning management systems is a plus.
• Proven ability to work effectively in an international environment is desirable.
• Demonstrable expertise in the development of knowledge products and/or scientific articles is an advantage.
• Fluent English and Turkish are necessary.

Disclaimer

Important Information for Permanent Residents of the US (Green Card Holders)

Under U.S. immigration law, accepting a staff position with UNDP, an international organization, can have significant consequences for U.S. permanent residents. UNDP advises applicants for all professional-level positions that they must renounce their U.S. permanent resident status and accept a G-4 visa, or have a valid application for U.S. citizenship prior to commencement of employment submitted.

UNDP is not in a position to provide advice or assistance in applying for US citizenship and therefore applicants are advised to seek advice from competent immigration lawyers regarding any applications.

Applicant information on UNDP rosters

Please note: UNDP reserves the right to select one or more candidates from this vacancy announcement. We may also retain applications and consider candidates applying for this position for other similar positions at UNDP at the same level and with similar job description, experience and educational requirements.

Non-discrimination

UNDP has a zero-tolerance policy towards sexual exploitation and misconduct, sexual harassment and abuse of power. All selected candidates will therefore undergo rigorous reference and background checks and are expected to adhere to these standards and principles.

UNDP is an inclusive, equal opportunity employer that does not discriminate on the basis of race, gender, gender identity, religion, nationality, ethnic origin, sexual orientation, disability, pregnancy, age, language, social origin or other status.

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