Data Scientist

The World Bank, Washington DC, United States

Skill Required:, IT and ICT
Preferred Experience: 
5 years
Closing Date for Applications: 
25th April, 2019

Job Description

Established in 1944, the WBG is one of the world’s largest sources of funding and knowledge for development solutions. In fiscal year 2018, the WBG committed $67 billion in loans, grants, equity investments and guarantees to its members and private businesses, of which $24 billion was concessional finance to its poorest members. It is governed by 188-member countries and delivers services out of 120 offices with nearly 15,000 staff located globally.

The WBG consists of five specialized institutions: the International Bank for Reconstruction and Development (IBRD), the International Development Association (IDA), the International Finance Corporation (IFC), the Multilateral Investment Guarantee Agency (MIGA), and the International Centre for the Settlement of Investment Disputes (ICSID). The World Bank is organized into six client-facing Regional Vice-Presidencies, several corporate functions and thirteen Global Practices to bring best-in-class knowledge and solutions to regional and country clients.

Poverty and Equity Global Practice

The Poverty and Equity GP, part of the EFI Cluster of Global Practices, plays three key –leading and supportive– roles: sectoral integrator at country level; generator of knowledge and dialogue; and operational solutions supporter. The country-level work of the Poverty and Equity global practice typically falls under one or more of the following three streams:

  • Laying the foundations for evidence-based policy by strengthening data on household welfare: this is the foundational work, mostly delivered through TA and occasionally through statistical capacity-building investment operations, to support the design and implementation of household surveys, provide advice on best-practice methodologies for estimating household welfare, poverty, and shared prosperity, and build capacity and strengthen country systems for collecting data on and monitoring household welfare.
  • Defining the agenda through integrative analysis and dialogue: this stream of work has focused on using the household-level data, wherever available, to undertake integrative analyses to inform the policy dialogue and advance the poverty reduction and shared prosperity agenda and priorities at the regional, national and occasionally sub-national levels.
  • Delivering operational solutions: this stream of work focuses on collaborating with internal and external partners to translate the upstream analytics into concrete implementable measures and support the implementation of particular interventions aimed at reducing poverty. This includes supporting the preparation of Systematic Country Diagnostics and Country Partnership Frameworks, as well as the analysis of poverty and social impacts of Bank operations.

The Poverty Global Practice is organized by both region and thematic Line, with regions managed by a Practice Manager. The development and flow of global knowledge within the practice is facilitated through four cross-cutting thematic lines, each of which is led by a thematic Lead Economist. These are:

  • poverty monitoring and statistical capacity building;
  • markets and institutions for poverty reduction and shared prosperity;
  • fiscal and social policy for poverty reduction and shared prosperity; and
  • managing risks for poverty reduction and shared prosperity.

Every member of the practice is affiliated with and participates in and contributes to the work of at least one of the thematic lines. In addition, the practice takes the lead in two corporate priority areas:

  • Data for Goals; and
  • Systematic Country Diagnostics.

Data for Goals

Embedded in the Poverty and Equity Global Practice, Data for Goals (D4G) is a team of data scientists and economists tasked with monitoring the World Bank Group’s (WBG) twin goals. The D4G team is responsible for developing tools, systems and protocols, in partnership with ITS, DEC teams, and the Regional Teams for Statistical Development, to automate and ease the workflow for the production of the Global and Regional poverty and shared prosperity monitoring of the World Bank. These data collections managed by the D4G team include the Global Monitoring Database (GMD) which are used to produce regional and global poverty estimates and inform high profile corporate products such WDI, Poverty and Shared Prosperity Report (PSPR) and the Corporate Scorecard (CSC).In addition, the team is also responsible for the regular analytical products such as macro-poverty projections, corporate score card indicators and global topical reports such as global profiles of poor, shared prosperity, at a glance notes etc., as well as to provide just-in-time requests to support and leverage the work of the Poverty GP Poverty Economists.

The D4G program is guided by the following principles:

  • Addressing World Bank Group’s commitment to monitor global poverty and shared prosperity by providing essential inputs to the poverty updates (such as the 2020 update), the Poverty and Shared Prosperity Report, and other corporate products.
  • Introducing innovations and technologies in welfare measurement and monitoring to amplify the impact of the WBG’s thought leadership in poverty and inequality measurement.
  • Increasing efficiency and exploiting economies of scale (coordination/collaboration and systems) by integrating regional teams within Poverty GP and engaging other colleagues such as the Global Solutions Group 1 (GSG1), the Development Data and Research Group (DECDG/RG) teams.
  • Promoting data access and use through data generation, harmonization, management and improved access by maintaining and creating WBG data platforms.

The Poverty & Equity GP is looking for a Data Scientist, based in Washington DC, to join SAR/MNA Regional Unit, and also contribute to the D4G program.

Duties and Accountabilities

The selected candidate will be based in Washington, DC. The Practice is seeking to recruit a data scientist with knowledge and experience in social sector indicators and analysis, strong quantitative methods and advanced programing skills, working experience in machine learning and statistical techniques. The selected candidate will also work on regional statistics programs and support country poverty programs. Experiences and skills required to conduct such programs will be a plus.

Specific responsibilities will include the following:

  • Conduct poverty, multidimensional poverty, shared-prosperity, and inequality data quality assessments and related analysis; contribute in reviewing and preparing technical notes and presentations relating to poverty, multidimensional poverty, shared-prosperity, inequality data; create meta-data and update electronic files on sources and definitions of data, as well as the methods used to adjust raw series and calculate indicators; contribute in reviewing and preparing technical notes and presentations relating to poverty, shared-prosperity, and inequality data; respond to data queries on poverty, shared-prosperity, and income inequality; and, participate in related workshops and training events.
  • Contribute to the expansion and improvement of the systematization of harmonization protocols and analytical tools for poverty, shared-prosperity and equity, as well as multidimensional poverty and geospatial analytics.
  • Identify opportunities to use AI, Machine learning and Big Data techniques in developing and implementing solutions for World Bank Poverty and Equity analytical works and projects, including through non-traditional data sources;
  • Support poverty programs in selected countries engaging in operational work with clients to design and deliver innovative analytical work, capacity building services, financial products and technical assistance using recent development in technologies and methods;
  • Build partnerships with other groups in the WB, including DEC teams and other GPs on poverty, shared-prosperity and equity monitoring issues and applications using recent technologies and methods;
  • Disseminate knowledge gained to country and regional teams in the practice, increasing the use of web-based visualizations on these indicators to tell clear stories;
  • Participate in activities and exchange information with other World Bank teams working on similar issues across sectors and Global Solution Groups.

Like all members of the Poverty global practice, the data scientist will also be expected to contribute to the global knowledge base of the practice.

Selection Criteria

  • A Master’s or PhD degree in Economics, Statistics or Computer Science or a closely related field, with a minimum of five years’ relevant experience, or equivalent combination of education and experience
  • In-depth knowledge on poverty measurement and analysis using household survey data, including the use of sampling weights, the construction and analysis of consumption aggregates, the derivation of absolute poverty lines, the estimation of poverty/inequality and welfare measures, and related econometric techniques; Experience with country poverty programs and regional statistics programs is desirable;
  • Understanding of the relationships between poverty and outcomes in related indicators of well-being in the areas such as education and health. Experience with related survey-based social and gender indicators and issues is considered a plus;
  • Experience building or working with interconnected IT architectures featuring i) interactive user interfaces, ii) various data sources, iii) automation of data generation and layout production processes, iv) workflow management, v) linkages with multiple software highly desirable;
  • Experience working with machine learning techniques and methods and applying them for household surveys or censuses in the context of poverty and shared prosperity; Excellent knowledge of Machine Learning, AI and Big Data techniques is strongly desired, such as experience and understanding of supervised and unsupervised machine learning, Time series, Natural language processing;
  • Advanced programming skills in modern statistics, scripts and programming languages such as Stata/Mata, R & Python with a publication record of user-written routines;
  • Commitment to teamwork, knowledge-sharing, and ability to influence across organizational boundaries; Experience in using Git or code sharing platforms;
  • Demonstrated ability to develop and implement complex tasks, including a track record of building partnerships and collaborations across institutional boundaries;
  • Demonstrated ability to multi-task and to effectively carry out multi-disciplinary analyses;
  • Excellent written and verbal communications skills. In particular, the candidate will exhibit the ability to communicate ideas effectively and to interpret statistical data quickly and clearly, including with informative graphs and charts; Experience working with BI tools and in preparing data visualizations such as Tableau, R-Shiny, D3, etc. is desirable;
  • Strong interpersonal skills and a demonstrated track record of meeting tight deadlines and of working in a multicultural team environment with multiple priorities;
  • Ability to work with staff from all levels and to mentor, coach and motivate more junior staff;
  • Reading, Writing and Spoken fluency in Portuguese, Arabic, French or Spanish is desirable.


The WBG core competencies are:

  • Lead and Innovate - Develops innovative solutions.
  • Deliver Results for Clients- Proactively addresses clients’ stated and unstated needs.
  • Collaborate Within Teams and Across Boundaries- Collaborates across boundaries, gives own perspective and willingly receives diverse perspectives.
  • Create, Apply and Share Knowledge- Applies knowledge across WBG to strengthen solutions for internal and/or external clients.
  • Make Smart Decisions- Interprets a wide range of information and pushes to move forward.

The World Bank Group is committed to achieving diversity in race, gender, nationality, culture, and educational background. Individuals with disabilities are equally encouraged to apply. Women and SSA/CR candidates are strongly encouraged to apply. All applications will be treated in the strictest confidence.


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