Evaluation Specialist Data Science

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Description

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Under the supervision of the senior evaluation specialist (head of impact evaluation and methods) the Evaluation specialist (data science) will provide support to organizational efforts in better utilization of AI/machine learning applications in evaluations to improve cost-efficiency of evaluation process and methods. Working collaboratively with the evaluation team in Evaluation office (NYHQ), the incumbent will support evidence generation and use in planned and ongoing global evaluations and impact evaluations, lead replication of tested and effective AI approaches across regions and country office teams.

In accordance with the UNICEF mission, guiding principles, standards, commitments, and accountability framework, and under the revised United Nations Evaluation Group norms and standards, the evaluation specialist (data science) will ensure that all products and applications conducted under her/his technical support and supervision are of the highest possible technical quality, relevance, timeliness, credibility, and utility.

Key functional responsibilities:

AI/Machine learning powered project development:

• Lead the experimentation, development and replication of AI/machine learning applications for a wide-range of evaluation purposes. Leverage these means for supporting and enhancing cost-effectiveness, rigorour, and credibility of UNICEF evaluations particularly those conducted in complex environments.
• Identify through consultation with global thematic evaluation teams, evaluation and academic partners other opportunities to create AI platforms with application of big data methods and emerging AI functionalities including but not limited to data mining, predictive analytics, deep machine learning for evaluative purposes such as scoping, evidence synthesis, counterfactual analysis among others.
• Use of Natural Language Processing (NLP) to analyze textual data from the Evaluation Information System Integration (EISI) database – internal database of UNICEF evaluation reports.
• Supervise and mentor consultants and EO interns in all aspects of data science and testing machine learning approaches. Collaborate with the regional and country office teams in joint data/innovation initiatives and pilots.

Data Analytics:

• Contribute to a wide range of advanced data analysis for complex rigorous evaluations and collaborate with global evaluation teams to scope, assess and identify relevant data sets to be used for evaluations.  
• Advise and guide the EO evaluation staff on using multifaced analytical approaches, including traditional statistical models, machine learning, etc., for the analysis and interpretation of data from different data sources, including surveys, big data, secondary data, etc.
• Lead data innovation in quantitative analysis protocols, including data gathering tools and methodologies collaborating with EO staff across thematic areas and topics.   
• Initiate and coordinate pilot studies and applications for using real-time data sources such as mobile technology as well as online media, social networks, remote imagery, geospatial data, administrative and institutional databases. 
• Contribute to data management, overseeing medium to large structured and unstructured datasets while maintaining data quality, security, and compliance.

Data Visualization and Learning:

• Lead and promote creative data visualization on digital and non-digital platforms in a variety of formats.
• Produce concise and high-quality methodological briefs, guidance and learning materials related to AI applications and other technical materials.

Capacity development and partnership:

• Support the development and roll-out of capacity-building activities that raise awareness and promote the use of AI/machine learning and rigorous data analytics in UNICEF evaluation.
• Initiate and leverage internal and external partnerships, including with other UNICEF divisions, multilateral and bilateral organizations, other United Nations agencies and academic institutions to advance an effective use of AI/machine learning application across all levels of the UNICEF evaluation function.

To qualify as an advocate for every child you will have…

Minimum requirements:

Education: 

• An advanced university degree (master or PhD) in sciences (e.g., mathematics, statistics, data science, economics, public policy, or a related field).

Work Experience:

• At least five years of experience in data science, data analysis and innovation preferably in development field and in areas relevant for UNICEF mandate (e.g. health, nutrition, education, child protection, water and sanitation and social protection).
• Proven record of applying AI/Machine learning in research and evaluation, preferably for development agencies.
• Experience using statistical computer languages to manipulate data and draw insights from large data sets (Scala/R/Python), Stata, SPSS and Databricks. Experience with data visualization libraries such as Matplotlib, Pyplot, or PowerBI is considered an asset.
• Ability to work cross functionally to define problem statements, examine collected data, build analytical models, and communicate final recommendations that drive decision making.
• Demonstrated ability to keep up to date with the latest skills and advancements in AI field finding creative ways to apply these advancements to research and evaluation.
• Proven record to work with internal and external stakeholders at multiple levels, including providing technical support and capacity building and establishing/managing external partnerships.

Language Requirements:

• Fluency in English; knowledge of another United Nations language (Arabic, Chinese, French, Russian or Spanish) is an asset.

Source: https://jobs.unicef.org/cw/en-us/job/577145

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