Maha Khader Dawas

Senior Statistician & Data Scientist with 24+ years of experience in official and development statistics across Jordan, Qatar, and the broader Middle East. Proven expert in poverty measurement, household survey analysis, and SDG indicator reporting, delivering data solutions in partnership with the World Bank, UNICEF, UNDP, UNFPA, UN Women, UNRWA, and ESCWA. Skilled in machine learning, predictive modeling, and econometric forecasting (ARIMA, ARDL, neural networks) using STATA, SPSS, PovMap, and DevInfo.

Former

Director of Data Management at Jordan's Department of Statistics; published author and award-winning researcher (2nd place, Arab AI Summit) in machine-learning-based poverty prediction. Author of "Introduction to Artificial Intelligence and Statistical Data Science" (Amazon).

Senior Statistician - UNDP, Jordan - Jordan

(2025-12 - 2026-02)

Aqaba Coastal Ecosystem Biodiversity Enhancement & Resilience Project

• Designed structured survey questionnaires to capture biodiversity and socioeconomic resilience data for a UNDP environmental project.
• Classified and coded open-ended survey responses, converting unstructured input into analyzable datasets.
• Authored descriptive statistical reports translating field data into actionable findings for project stakeholders.

Senior Statistician - National Planning Council, Qatar - Qatar

(2021-02 - 2025-10)

• Processed and cleaned large-scale survey microdata in STATA, preparing analysis-ready datasets for the Labour Force Survey (LFS) and Household Income & Expenditure Survey (HEIS).
• Calculated and reported SDG indicators from LFS and HEIS data, supporting Qatar's national 2030 monitoring framework.
• Produced descriptive statistical reports measuring standard of living and user satisfaction with national statistical data.
• Extracted statistical tables and key indicators, and designed survey questionnaires with embedded audit/validation rules to improve data quality before field deployment.
• Served as technical member of Qatar's national Multidimensional Poverty Index (MPI) and SDG committees.

Director, Data Management Directorate - Department of Statistics, Jordan - Jordan

(2002-03 - 2020-12)

Progressive leadership: Field Researcher -> Division Head -> Directorate Director

• Directed the Business Records, Data Management, and Gender Statistics divisions, supervising technical and administrative reporting across the directorate.
• Built a centralized civil registry and population-frame database, establishing electronic connectivity with all government agencies to streamline inter-ministerial data flows.
• Audited and quality-assured incoming administrative data from government ministries, and tracked delivery of the National Statistics Strategy 2018-2022.
• Built predictive statistical models using machine learning and artificial neural networks, including an award-winning poverty-prediction model (2nd place, Arab AI Summit 2019).
• Applied an ARIMA time-series model to forecast Jordan's unemployment rate over a 10-year horizon.
• Developed an ARDL econometric model to identify the key determinants of poverty in Jordan.
• Led national poverty analysis, extracting poverty indicators and mapping poverty pockets via PovMap and Small Area Estimation (STATA) in collaboration with the World Bank (2017-2018).
• Authored Jordan's official poverty reports across 5 survey cycles (2006-2021), plus thematic reports on feminization of poverty and quality-of-life indices.
• Built bilingual (Arabic/English) poverty and quality-of-life indicator databases in DevInfo.
• Served as technical member of two national Poverty Reduction Strategies (2013-2025).
• Partnered with the World Bank to redesign the 2017 HEIS using updated methodology (sampling, questionnaire design, data collection, and entry).
• Performed missing-data imputation and computed adjusted survey weights in SPSS/STATA to ensure representative national estimates.
• Collaborated with Oxford University (OPHI), ESCWA, and the League of Arab States to produce Jordan's National MPI (2017-2018) and regional Arab MPI estimates.

Statistical Consultant - Poverty Analysis - UNRWA Headquarters, Jordan - Jordan

(2014-01 - 2016-12)

• Audited and cleaned raw survey data across three fields (Jordan, Lebanon, West Bank) in SPSS, deriving poverty lines and indicators and authoring comparative descriptive reports for each field.

Statistical Consultant - HIES - National Bureau of Statistics, Abu Dhabi - Abu Dhabi

(2015-01 - 2015-12)

• Processed and cleaned raw Household Income & Expenditure Survey microdata in SPSS for the UAE statistical authority.

B.A. - Financial & Banking Sciences - Yarmouk University, Faculty of Economics