Research Fellow in Data Analytics

il y a 1 mois


Gouvieux, France The Aga Khan Academies Temps plein

3786BR

University of Central Asia

The position

UCA Background:

The University of Central Asia (UCA) was founded in 2000 as a private, not for profit, secular university through an International Treaty signed by the Presidents of Tajikistan, Kyrgyzstan and Kazakhstan, and His Highness the Aga Khan; ratified by their respective parliaments, and registered with the United Nations. The Presidents are the Patrons of the University and His Highness is the Chancellor. UCA’s mission is to promote the social and economic development of Central Asia, particularly its mountain communities, by offering an internationally recognised standard of higher education, and enabling the peoples of the region to preserve their rich cultural heritage as assets for the future. UCA brings with it the broader commitment and partnership of the Aga Khan Development Network. For more information: 

Summary of Position:

The University of Central Asia is currently seeking a qualified candidate to fill a full-time position within the Institute of Public Policy and Administration (IPPA). Established in 2011, IPPA is dedicated to enhancing public policy in Central Asia by conducting comprehensive analyses of regional policy challenges. It strives to bolster the analytical capabilities of governmental and civil society entities, facilitating evidence-based decision-making through professional development initiatives. IPPA disseminates its findings through a series of rigorously peer-reviewed research papers covering a spectrum of social and economic issues, as well as public administration and policy matters pertinent to Central Asia. 

The Research Fellow will serve as a crucial contributor to the institute's research initiatives, actively advancing its agenda through the application of specialized expertise. Their responsibilities will include active participation in ongoing research projects, where they will employ sophisticated quantitative methodologies and data analysis techniques to derive meaningful insights informing policy formulation and implementation, based on data from across the region. Furthermore, the Fellow is anticipated to possess the potential for or a track record of successful grant acquisition, from research and development donors. Alongside project contributions, the Fellow is expected to allocate a portion of their time to the establishment of the Data Hub at the Graduate School of Development, thereby contributing to the institute's broader institutional goals and to teaching on the School’s graduate and executive programmes.

Main Duties and Responsibilities

Develop and implement own research agenda predicated on peer-reviewed publication and grant capture activities.  Support existing and new projects, with custom forecasting and quantitative research, focusing on tasks such as data collection, cleaning, analytics, and econometric modelling, under the guidance of principal investigators.  Be familiar with key terms and concepts of Data Science and Machine Learning. Develop and maintain econometric models, including those with machine learning elements like cross validations and bootstrapping. Undertake relevant teaching and supervision on the School’s graduate and executive education programmes.  Support curriculum development and quality assurance in learning and teaching. Contribute to the establishment and management of a proposed Data Hub at the Graduate School of Development, including the collection, organization, and dissemination of relevant data to support internal and external research activities.  Engage in knowledge exchange activities, such as seminars, workshops, and conferences, to disseminate research findings and foster dialogue with stakeholders in academia, government, and civil society. Department: Institute of Public Policy and Administration (IPPA)
Reports to: IPPA Team Lead
Duty station: Bishkek, Kyrgyz Republic
Deadline: May 22, 2024

The requirements

Qualifications and Skills: 

An advanced degree in statistics, mathematics, econometrics, applied econometrics, applied economics, economics or a related quantitative field. A relevant Ph.D. qualification in Economics/Mathematics/Statistics is desirable and usually is a requirement for a Research Fellow position. Otherwise, a candidate who earned Ph.D. in other fields (e.g., Social Sciences) should be able to demonstrate his/her work (e.g., part of Ph.D. Thesis, working paper, publication, etc.) of application of advanced quantitative methods. Alternatively, a minimum of five years of experience working in data analytics or related area and with evidence of grant capture and/or publication may be considered equivalent. Possess a comprehensive grasp of one or more of macro- and/or microeconomic, demographic, climate, and survey data concepts, along with familiarity with key data series at both local and regional levels. Proficiency in Microsoft Excel, including experience with formula auditing, data manipulation, and advanced functions. Proficiency in MS Excel VBAis desirable. Proficiency in statistical analysis and econometric modelling. Familiarity with machine learning models (e.g., Supervised, Unsupervised and Reinforcement Learning) or estimating econometric models (e.g., Regression analysis, Panel Data, Principal Component Analysis, Instrumental Variables, Difference-in-Difference, Time-Series and its applications) with ML elements, like cross validations, bootstrapping methods is advantageous. Proficiency in at least one programming language, preferably R or Python. Working knowledge of key R libraries like tidyverse and ggplot2 (if proficient in R) or key Python libraries like Pandas, Numpy, and Matplotlib (if proficient in Python). Familiarity with R-Markdown (if proficient in R) or Jupyter Notebook (if proficient in Python). Some familiarity with SQL for database querying is beneficial. Excellent communication (verbal and written) skills, including strong presentation abilities. Experience in grant capture is desired.  A high standard of written and spoken English is essential for this role. The ability to work across disciplinary boundaries and collaborate with colleagues from across the Graduate School is desirable.  Utilize programming languages such as STATA, SPSS, R or Python for statistical analysis and modelling, with proficiency in key libraries like tidyverse, ggplot2 (for R), Pandas, Numpy, Matplotlib (for Python). Utilize SQL to extract and manipulate data with programming abilities from databases efficiently.

Languages: 

Advanced English is essential. Advanced Russian is strongly preferred.  Working knowledge of Kyrgyz, Tajik, and/or Kazakh would be an asset.

How to Apply

Candidates from the founding countries of UCA: Kyrgyzstan, Tajikistan, and Kazakhstan are encouraged to apply for the position.

Applications will be reviewed when received. Early applications are strongly encouraged. Only shortlisted candidates will be contacted.

Review other job vacancies at: 

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