Consultant

Job Summary

The Consultant will deliver decision-oriented analytical support to MINEDUC while strengthening sustainable, in-house data analysis capacity within REB and NESA. Key duties include cleaning and merging large-scale educational datasets, executing reproducible statistical code scripts, designing mixed-methods implementation research, modeling value-for-money and program scaling costs, and engineering a comprehensive technical handover package to ensure long-term institutional sustainability.

Qualification

• Educational Profile: Advanced university degree (Master’s or Ph.D.) in Education (with a clear quantitative research track), Statistics, Applied Statistics, Economics, Econometrics, Data Science, or a related social science field emphasizing data mechanics.
• Statistical Language Proficiency: Advanced, expert-level commands in Stata and/or R environments to build fully documented, transparent, and reproducible data code.
• Core Competency Matrix: Advanced data curation, mixed-methods research design, micro-costing analysis, data visualization, technical writing, and data protection management.
• Language Requirements: Full professional fluency in English (written and verbal) is required. Working knowledge of French is considered a highly valuable asset.

Experience

Candidates must demonstrate a track record of running high-level quantitative research pipelines and working within public education sectors:

Quantitative Research & Data System Curation

• Professional Longevity: A minimum of eight (8) years of progressive, relevant experience in education research, implementation research, program evaluation, or learning assessment analysis.
• Contextual Domain Experience: Direct, documented experience conducting educational research or program evaluations within Rwanda or matching sub-Saharan development contexts.
• Large Dataset Integration: Proven ability to clean, validate, merge, and structure large-scale data points, translating complex findings into concise, policy-aligned insights for senior government decision-makers.
• Mixed-Methods Evaluation Architecture: Practical experience linking quantitative student datasets with qualitative field evidence, such as classroom lesson observations and school-level learning process tracking.

Embedded Technical Assistance & Financial Modeling

• Government Capacity Building: A proven history of operating as an embedded advisor, delivering hands-on mentoring, joint analysis, and co-working support to Ministry of Education staff or state statisticians.
• Routine Institutionalization: Desirable experience establishing long-term reporting cycles, automating data aggregation routines, and configuring standard operating procedures (SOPs) within government ministries.
• Costing & Value-for-Money (VfM) Analysis: Direct experience compiling cost drivers, estimating per-pupil unit costs, and developing scenario-based projections to inform national program scale-up decisions.
• Data Ethics & Governance: Clean record of handling sensitive information, executing strict data privacy frameworks, managing child-safeguarding boundaries, and upholding high quality-assurance metrics.

Key Responsibilities

Policy-Relevant Evidence Generation & Analytics

• Clean and Standardize Datasets: Process, merge, and clean massive student and school-level implementation datasets to ensure tracking accuracy for the national remedial learning program.
• Program Reproducible Scripts: Author and maintain clean, well-commented Stata or R script libraries to generate automated, transparent analytical outputs.
• Integrate Mixed-Methods Data: Merge quantitative learning outcomes with qualitative field assets—including structured lesson observations—to pinpoint program bottleneck drivers.
• Model Scale-up and Unit Costs: Lead detailed costing and value-for-money analyses, mapping cost drivers to deliver scenario projections for national policy adjustments.

Government Institutionalization & Capacity Building

• Embed In-House Mentorship: Conduct daily co-analysis and structural mentoring modules alongside designated analysts from MINEDUC, REB, and NESA.
• Sustain Analytical Routines: Build and deploy repeatable reporting cycles and automated tracking templates to institutionalize data workflows within the ministries.
• Draft Standard Operating Procedures: Author comprehensive SOPs covering data cleaning, privacy protections, and statistical reporting to remove technical dependencies.
• Deliver Handover Engineering: Construct and execute a final, turn-key technical handover package containing reusable data templates and documentation scripts before contract completion.

Skills Required:

• Economics / Statistics