QuintEdge
Finance Jobsby QuintEdge

Quantitative Lead - Primary Research | Onsite | Gurgaon

Outline India

Gurugram, Haryana, India

Full TimeQuantitative Finance

Posted 4 June 2026

Job description

Walkin interviews are open from Mon-Fri at our Gurgaon office between 9:30am • 11am Role: Quantitative Lead • Primary Research You will manage large survey datasets, run quantitative analysis,perform quantitative analysis using STATA software, Python is a plus, and support the full research cycle—from instrument design and field deployment to cleaning, analysis, and reporting. This is not a desk‑only role; travel to field sites for training and monitoring is an integral part of the job. Key Responsibilities I. Data Management & Analysis Clean, label, and analyze quantitative data using STATA (Python a plus). Produce clear visualizations and contribute to research reports. Build/deploy survey tools in SurveyCTO; design/test XLSFormsMaintain data quality across the entire pipeline, from field collection to analysisManage and monitor survey datasets across multiple concurrent projects II. Field Operations & Project Management Coordinate with field supervisors on daily data‑quality reviews and issue resolutionAssist in planning field budgets and timelines, and help oversee end‑to‑end project delivery on assigned studiesTravel to field sites for enumerator training and data monitoring and train teamsReview survey instruments and questionnaires from clients and support translation Offered CTC - Upto 15LPA Work days • 5 days | Onsite Location • Gurgaon, Sec-43 Interested candidates can share their applications on hr@outlineindia.com . Shorlisted applicants will be contacted for in-person discussion. Qualifications 8+ years in quantitative research (development, policy, or social sectors preferred). Strong Stata proficiency (cleaning, analysis, management); Python beneficial. Hands-on experience in SurveyCTO & STATA. Python is a plus Experience working with international clients or large institutions (World Bank, UNDP, etc.)Experience in M&E project settings with managing large, complex datasets from field surveys and randomized evaluations