TERMS OF REFERENCE (TORs)

Transcription

1 TERMS OF REFERENCE (TORs) OVERVIEW TITLE LOCATION OF ASSIGNMENT LANGUAGE(S) REQUIRED TRAVEL DURATION OF CONTRACT SECTION & UNIT CONSULTANT REPORTING TO Data Science Researcher & Lead analyst for Information Poverty Phase Classification New York, NY English Flexibility to travel if needed 11.5 months Office of Innovation Co-lead Innovation Unit BACKGROUND & RATIONALE In the same way that we have tools to measure nutrition access (kcal/day) and identify populations at risk of famine, UNICEF is developing tools to measure information access (kb/day) and identify populations suffering from severe information deprivation. Access to information is critical in allowing families to make decisions regarding health, finances, education, etc., and as more and more of the global population is connected via mobile phones and internet, the disparity between those with access and those without is growing exponentially. UNICEF and partners need to be able to reach the most deprived populations with essential information and services. The Information Poverty Phase Classification (IPPC) is a new tool focused on identifying and targeting severe information deprivation. It aims to provide actionable insights that can benefit vulnerable populations and populations in crisis through a "convergence of evidence" approach, that includes both traditional data and measures (such as government data, ITU statistics, etc.) as well as new and exploratory data sources and methods (such as satellite images and mobile phone data).the IPPC brings together all of these sources of evidence to produce a quantitative and qualitative measure of information deprivation, considering key actionable dimensions such as: 1. Information reach (e.g. is critical information from UNICEF and governments campaigns reaching vulnerable children) 2. Information search (e.g. can children seek out and find relevant information) 3. Connectivity to bigger community (e.g. can children share problems and ideas with relevant actors) About UNICEF Innovation: UNICEF Innovation is an interdisciplinary team of individuals around the world focused on identifying, prototyping, and scaling technologies and practices to improve the lives of children and young people. We

2 leverage our network of local entrepreneurs, academics, private sector companies, and others to test promising emerging technologies, to incubate prototype applications of these to assist UNICEF programs and to support scale up of successful prototypes to the rest of the organisation. PURPOSE The purpose of this consultancy is twofold: 1. To conduct research and analysis of survey and other suitable data for the pilot of the Information Poverty Phase Classification (IPPC). The pilot will focus on identifying and analysing relevant data from three participating countries and refining the methodology for IPPC. 2. To provide support on existing data science projects as well as leading one new line of research based on organisational needs and after a period of surveying opportunities including large scale text analysis, disease modelling and analysis of large scale social behaviour as reflected in patterns of social network interactions. EXPECTED RESULTS: (MEASURABLE RESULTS) - Coordination of IPPC stakeholders including UNICEF country offices, other UN agencies and statistical agencies to identify relevant and useful data-sources to be compiled in an evidence table for the first pilot country and eventually extended to second and third countries - Documentation of IPPC learnings in a comprehensive report and communication of findings to stakeholders. - Development of infrastructure to collect, house and analyse non-traditional forms of data such as text documents and social media interactions. Code will be documentation and compiled in an open-source repository. - Communication of findings in the form of technical documentation and a scientific publication and also communicated in a verbal form to both internal and external stakeholders. DUTY STATION NYHQ TIMEFRAME DELIVERABLES - Identification and compilation of relevant traditional information poverty data sources for first pilot country - Completion of information poverty data and evidence table for first pilot country - Recommended additions/revisions to variables and indicators in the current Information Poverty Phase Classification (IPPC) - Identification of relevant data sources for other data science projects - Proposed methodology for applying statistical modeling and innovative data analytics to obtain estimates as required; Deadline End of 1 st month End of 2 nd month Page 2 of 5

3 - Independent research report and proposal of new approaches on measurement and data issues related to the specific dimensions of the IPPC; - Application of traditional statistical modeling and innovative analysis techniques to obtain estimates as required by the analyses; - Produce tables, graphs and other statistical information for the chapters of the Report; - Draft texts to assist in the interpretation of statistical analyses when necessary - Phase Classification conducted on pilot country data (in conjunction with IPPC team) - Participation in IPPC strategic meeting to develop next iteration of framework - Submit comprehensive list of potential data sources and survey of cleaning and merging requirements for other data science projects to Lead Research Scientist - First draft of IPPC data and evidence template - Identify relevant data science algorithms and methodologies from scientific literature to be developed -Identification and compilation of relevant data sources for pilot countries 2 and 3 - Completion of data and evidence table for pilot countries 2 and 3 - Second draft of data and evidence template for countries 2 and 3 - Develop new methodologies and algorithms to leverage data science to assist UNICEF programs -Draft report documenting IPPC methodology and providing guidance for replications -Document new methodologies and algorithms to leverage data science to assist UNICEF programs -Final documentation and report on IPPC -Development of data science infrastructure to acquire and store data from APIs and other sources Draft of scientific paper on findings and methodologies for use of Big Data for development Development of prototype visualisation tools to navigate large datasets Iteration of visualisation platform and backend based on user feedback Iterate and develop documented methodologies for big data analysis Submission of final scientific report and code repository Submission of handover report detailing lessons learned and scientific findings on the use of data for UNICEF programs TOTAL End of 3 rd month End of 4 th month End of 5 th month End of 6 th month End of 7 th month End of 8 th month End of 9 th month End of 10 th month End of 11 th month End of 11.5 month 241 days KEY COMPETENCES, TECHNICAL BACKGROUND, AND EXPERIENCE REQUIRED DEADLINE - Master s degree from a recognized university, in economics, statistics, demography or other related quantitative or social science disciplines with a strong training in applied statistics/quantitative analysis. - At least two years of relevant work experience i.e. project management, data analysis or statistics; Page 3 of 5

4 - Demonstrated sustained high-quality work using open source software for analyzing data (such as R or Python), and other standard office software such as Excel and Word; - Demonstrated outstanding analytical and quantitative skills, and the ability to conduct independent research; - Experience in using socio-economic indices; identifying existing survey tools and statistics. - Familiarity with emerging methods and research in area of computational social science and big data analytics - Familiarity with non-traditional data sources such as social media, mobile phone metadata, web searches, satellite imagery. - Experience of using household survey data for estimation and analysis of models, distributions and population parameters is preferred - Familiarity with phase classification tools and methodologies such as the Integrated Food Security Phase Classification preferred - Experience of working in UNICEF program countries is an asset How to apply: Interested and suitable candidates are requested to send their applications with Subject Data Science Researcher & Lead analyst for Information Poverty Phase Classification to: jobsugic@gmail.com on or before 30 April Applications must include the following: Cover letter P11 ( CV expected monthly rate in USD (total / all-inclusive rate) Incomplete applications will be disqualified. Applicants must clearly indicate the position applied for and use this order to name file attachments: Firstname_Lastname followed by document e.g. Gold_Mukasa_CV or Gold_Mukasa_CoverLetter. Only short listed candidates will be contacted. Visit us at and Page 4 of 5

5 UNICEF is committed to achieving workforce diversity in terms of gender, nationality and culture. Individuals from minority groups, indigenous groups and persons with disabilities are equally encouraged to apply. All applications will be treated with the strictest confidence. Page 5 of 5