Key Responsibilities

Study Design Preparation

Support drafting of research protocols, sampling plans and data collection tools.
Conduct background literature reviews and compile secondary datasets.
Preparation of assessment instruments based on the pedagogical understanding

Field Partner Coordination

Liaise with survey vendors and internal CSF teams to schedule and enable data collection.
Track fieldwork progress in real time and flag deviations early to the supervising PM/PL.

Data Management Quality Assurance

Under the guidance of a PM/PL, clean raw quantitative and qualitative datasets, run basic validity checks, and maintain version controlled code and documentation.
Participate in enumerator training programs and support the adoption of digital data collection platforms as required.
With close supervision from a senior team member, produce descriptive statistics, thematic matrices and draft visualisations using Stata/R/Excel.
Contribute draft sections (methods, results tables, field notes) and slide decks for reporting; senior colleagues will refine the narrative and recommendations.

Team Knowledge Support

Maintain shared repositories of tools, codebooks and SOPs.
Document lessons learned in internal brownbag sessions.
Required Skills Qualifications
Education: Bachelors degree in economics, statistics, public policy, education or a related discipline. A Masters degree / relevant coursework in research methods is an advantage.
Experience: 02 years in research, ME or data oriented roles
or
relevant internships/academic projects. Demonstrated understanding of the Indian schooleducation landscape is preferred.
Foundational Research Knowhow: Working understanding of the research processdefining objectives, choosing methodologies, designing tools, overseeing data collection, cleaning, analysis and reporting.

Technical:

Proficiency with Microsoft and GSuite for data cleaning and visualisation. Foundational working knowledge of Stata or R will be highly preferred. and Demonstrated evidence of deepening expertise through onthejob coaching and self-learning will be looked out for.
Readiness to learn and rapidly adopt digital data collection platforms (e.g., SurveyCTO, Kobo, Tangerine) and qualitative coding tools (e.g., NVivo, Dedoose) as required.
Core Competencies:
Bias for Action:
manages own tasks endtoend, proactively raises blockers.
Problem Solving:
breaks down operational issues, uses data to propose fixes.
Learning Agility:
learns and unlearns methodologies quickly, experiments with more efficient processes.
Communicating Effectively:
produces clear slides/briefs/documents, tailors language for other teams/stakeholders.

Desired Qualities

Strong interest in research and programme evaluation and passion for equity in education.
Growth mindset with the ability to learn and unlearn rapidly, maintaining a deep eye for detail.
Collaborative spirit when working within the RMEAL team, and while coordinating with vendors and other stakeholders.
Resilience and attention to detail under tight timelines and in complex field settings.

Project Associate - RMEAL