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Leadership & Technical Expertise

DataTech Solutions Myanmar is an expert-led research data consultancy led by Nay Lin Soe, providing institutional survey technology and analytical leadership.

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Nay Lin Soe

Lead Research Data & CAPI Specialist

Executive MBA (EMBA) Yangon University of Economics
B.C.Sc (Hons), Computer Science University of Computer Studies, Yangon
Professional Training & Specialization ESOMAR Foundation / MMSA Questionnaire Design • Sampling • Statistics & Hypothesis Testing
KoBoToolbox (ToT) ODK Central SurveyCTO SurveyToGo CSPro SPSS Stata Power BI XLSForm
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Professional Background & Leadership

Nay Lin Soe is a senior Social Research, Data Management, and Monitoring & Evaluation (MEAL) specialist with over 17 years of experience architecting quantitative data systems across Myanmar and Southeast Asia.

Throughout his career, he has directed research data departments, managed large-scale field quality control operations, programmed advanced CAPI mobile applications, and authored automated analytical syntaxes for major international development partners, UN agencies, INGOs, and research entities.

Core Areas of Technical Specialization:

Data Department Leadership: Managing multi-disciplinary teams, timeline enforcement, QA protocols, and secure data storage governance.
Advanced CAPI & XLSForm Logic: Validated cascading choices across 330+ townships, dynamic household rosters, regex constraints, and bilingual Myanmar Unicode scripts.
Real-Time Quality Control: Automated submission monitoring, GPS outlier detection, duration speeder flags, and supervisor callback workflows.
Reproducible Statistical Processing: SPSS (`.sps`) and Stata (`.do`) syntax authoring for recoding, weighting, multiple-response sets, and donor-ready tables.
Institutional ToT Capacity Building: Facilitating Training of Trainers cohorts and mentoring MEAL practitioners across Myanmar.

Our Data Engineering Philosophy

At DataTech Solutions Myanmar, we believe that research credibility is engineered from the ground up. Reliable statistical decisions require flawless questionnaire logic, real-time field error interception, and reproducible data transformations.

By replacing error-prone manual spreadsheets with automated code and robust mobile validation, we ensure your research outputs stand up to rigorous peer review and donor audits.