Quantitative Research Assistant - Urban Impact Lab

Location: Islamabad
Start Date: Immediate

About the Role

Urban Impact Lab is seeking a proactive Research Assistant to support a large-scale INGO-funded primary healthcare service delivery project across two provinces. This is an excellent opportunity for an early-career researcher to gain hands-on experience in development sector research while working on a high-impact international project.

The ideal candidate is a self-starter who doesn't just complete tasks but actively looks for ways to improve processes and add value. You'll work directly with senior researchers, handling both the quantitative backbone of our research and various project coordination tasks that keep our work moving forward.

Key Responsibilities

Quantitative Research (60%)

• Clean and manage large datasets from baseline and endline surveys
• Conduct data quality checks and identify inconsistencies
• Perform descriptive statistical analysis and create data visualizations
• Support impact evaluation analysis including difference-in-differences, matching, and RCT analysis
• Prepare data tables and figures for reports and presentations

Project Support (30%)

• Review and provide feedback on project documents
• Draft sections of research reports and policy briefs
• Coordinate with field teams and follow up on project deliverables
• Support preparation of presentations and meeting materials
• Maintain project documentation and research logs

General Research Support (10%)

• Assist with literature reviews and background research
• Handle ad-hoc analytical requests
• Support other Urban Impact Lab projects as needed

Required Qualifications

Education & Experience

• Bachelor's degree in Economics, Statistics, Public Policy, or related field
• 1-2 years of relevant work experience in research or data analysis
• Understanding of research methodologies used in development sector quantitative work

Technical Skills

• Proficiency in Stata (required)
• Advanced Excel skills
• Understanding of impact evaluation concepts (DiD, RCTs, matching methods)
• Ability to clean and analyze survey data independently

Core Competencies

• Self-motivated problem solver: You see a dataset and think "what story does this tell?" You notice inefficiencies and propose solutions without being asked
• Strong analytical thinking: Ability to spot patterns, inconsistencies, and draw meaningful insights from data
• Excellent written and verbal communication skills in English
• Ability to work independently, manage multiple deadlines, and prioritize tasks
• Comfort with ambiguity and flexibility to handle diverse tasks outside typical research work

Preferred Qualifications

• Knowledge of R or Python for data analysis is a plus point
• Experience with Power BI or willingness to learn quickly
• Familiarity with health systems or service delivery research
• Experience working with large household survey datasets
• Basic understanding of sampling design and survey methodology
• Prior exposure to development sector projects