Analyst- Social Protection And Jobs (Global) at Genesis Analytics

•  The Social Protection & Jobs (SPJ) team sits within Genesis's Human Development practice and works at the intersection of poverty analysis, social systems design, and public policy. We partner with governments, multilateral institutions, and development partners across Africa, the Middle East, and Asia to build social protection systems that are inclusive, integrated, shock-responsive, and fiscally sustainable.

 Our work spans four interconnected areas:

• Designing integrated, shock-proof social protection systems — diagnosing gaps, developing legislation and policy, expanding labour and employment support, and extending social insurance to informal sector workers et.c.
• Unlocking fiscal space — conducting public expenditure reviews, fiscal space analysis, and cost-benefit analyses to help governments sustainably finance and expand social protection coverage.
• Building foundational digital delivery systems — strengthening social service workforces, building modern civil and social registries, payments infrastructure, case management systems, and integrated service referral networks.
• Linking humanitarian and development action — embedding shock-responsive and anticipatory action into system design, integrating disaster risk finance and climate-linked cash transfers, and working in fragile and conflict-affected settings (FCAS).

Requirements

• We are looking for a quantitatively strong Analyst to join the SPJ team. You will contribute to research and analysis that informs social protection system design, programme evaluation, fiscal diagnostics, and digital delivery assessments across our project portfolio.
• This is a research and analytical role with real policy influence. You will work directly with senior consultants and government counterparts on assignments that shape how governments design, finance, and deliver social protection to vulnerable populations.

Your responsibilities will include:

• Conducting quantitative analysis to assess social protection coverage, benefit adequacy, targeting accuracy, and fiscal sustainability — including microsimulations, proxy means test evaluations, and poverty and vulnerability profiling.
• Analysing household survey data (e.g., LSMS, DHS, national income surveys) using statistical software (Stata, R, or Python) to produce evidence on poverty, vulnerability, and social protection outcomes.
• Supporting public expenditure reviews and fiscal space analyses, including modelling the cost of expanding social protection programmes under different scenarios.
• Contributing to assessments of social registry and MIS design, beneficiary identification mechanisms, and digital delivery system performance.
• Synthesising quantitative and qualitative evidence into policy-relevant reports, briefs, and presentations for government and donor clients.
• Supporting the design and implementation of monitoring and evaluation frameworks, including defining indicators, data collection approaches, and results measurement.
• Engaging with government counterparts and development partners under the supervision of senior team members.
• Genesis consultants carry a balanced combination of powerful intellect, strong technical skills, and a consulting character to match. 

Successful candidates for roles at Genesis:

• Are passionate, self-motivated problem-solvers
• Value integrity and exhibit ethical behaviour
• Are analytical thinkers and fast learners with an excellent academic record
• The successful candidates will thrive in a fast-paced environment, enjoy the flexible nature of the job, and like to hit the ground running. You are pro-active and hands-on, with the ability to not only work effectively as part of a team, but also to motivate the team and ensure they can excel. 

Preferred Qualifications

• Education: Minimum bachelor's degree in Economics, Statistics, Public Policy, Development Studies, or a related quantitative field. A master's degree or postgraduate coursework with a strong quantitative component is advantageous.
• Technical skills: Demonstrated proficiency in Stata, R, or Python for data analysis. Experience with household survey datasets (LSMS, DHS, HIES) is a strong advantage.
• Certifications or specialisations in social protection, development economics, data science, or programme evaluation are welcome.

Necessary

• Strong quantitative foundation: Demonstrated ability to work with large datasets, conduct regression analysis, and produce statistically rigorous outputs. Proficiency in at least one of Stata, R, or Python is required.
• Analytical thinking: Ability to move between data, evidence, and policy implications — discerning patterns in complex datasets and translating them into actionable insights.
• Research experience: Exposure to primary or secondary data collection, survey analysis, or economic/social research in an academic, government, or consulting context.
• High-quality outputs: Commitment to accuracy and rigour in all work products, including under tight deadlines.
• Communication skills: Ability to present quantitative findings clearly in written and visual formats to non-technical audiences.
• Proactivity and collaboration: Willingness to contribute across a multidisciplinary team and take initiative on tasks.

Desirable

• Familiarity with social protection data and methods: Experience with proxy means testing, beneficiary targeting analysis, social registry design, or social transfer programme evaluation.
• Knowledge of labour market analysis: Understanding of informal sector dynamics, employment diagnostics, or labour force survey analysis.
• Exposure to government or policy work: Experience engaging with government departments, ministries, or public sector institutions in a research or advisory capacity.
• Experience with digital delivery systems: Familiarity with MIS design, payments systems, or digital identity and registration processes in a development context.
• Humanitarian-development nexus: Understanding of shock-responsive social protection, adaptive programming, or work in fragile and conflict-affected settings.