Quantitative Analysis Specialist

**Background**

SLM is a monitoring, evaluation, and learning firmthat provides bespoke solutions to complex global challenges. We partner with leading international donors, multilateral organizations, and implementing partners to advance evidence-based decision-making.

SLM is currently preparing a proposal for a large-scale, mixed-methods Situation Analysis focusing on education access, continuity, and vulnerability in Myanmar. This highly strategic study will inform sector-wide planning, resource allocation, and resilience programming in a complex and evolving operating environment.

We are seeking exceptional analytical and research professionals to join our proposed team. The anticipated period of performance is **June 2026 to January 2027.**

**Role Overview:**

The Quantitative Analysis Specialist will lead the rigorous secondary analysis of large-scale national household datasets. You will be responsible for extracting insights on education participation, dropout rates, and household expenditure dynamics to identify key vulnerabilities across geographic and socioeconomic groups.

**Key Responsibilities:**

- Conduct complex statistical analysis of 2025 household-level microdata, accounting for survey design and weighting procedures.
- Examine indicators related to education participation, interruption, non-participation, and vulnerability exposure.
- Produce highly disaggregated findings (by geography, gender, urban/rural, and socioeconomic status).
- Draft clear, concise interim technical notes and contribute written quantitative sections to the final analytical report.

**Required Qualifications:**

- **Language & Communication:** Full professional proficiency in written and spoken English. Ability to translate complex statistical findings into accessible written narratives.
- **Education:** Advanced university degree in Statistics, Economics, Data Science, or a related discipline.
- **Experience:** Minimum five (5) years of experience analyzing large-scale household or social sector datasets.
- **Technical Expertise:** Demonstrated experience working with complex survey designs and weighting procedures; proficiency in commonly used statistical software (e.g., Stata, R, SPSS, Python).
- **Desirable:** Specific experience analyzing education-related indicators and conducting multivariate or regression-based analysis.