ALG Head of Impact

Your tasks

Build the evidence and trust architecture

• Build the trust infrastructure for ALG’s next phase of scale: the methodologies, systems, validation partnerships, dashboards, governance, and public-facing evidence needed to make our impact claims credible under scrutiny.
• Develop and own ALG’s impact methodology, including approaches to data collection, verification, sampling, extrapolation, attribution, contribution, confidence intervals, error margins, data quality, and limitations
• Define the standards for what ALG can claim internally, what can be shared with donors, what requires caveats, and what is ready for external publication or independent validation.
• Move ALG’s impact narrative beyond short-term placement statistics to include income lift, economic mobility, promotions, entrepreneurship, household uplift, family support, resilience, and long-term career progression.
• Strengthen internal alignment around core impact definitions, metrics, data sources, reporting standards, and evidence thresholds, ensuring leadership, fundraising, product, and program teams are working from a single source of truth.

Lead rigorous evaluation and external validation

• Design and lead a rigorous research and evaluation agenda, including RCTs, quasi-experimental studies, tracer studies, longitudinal research, employer studies, learner surveys, and mixed-methods evaluation.
• Identify which research methods are appropriate for different programs, geographies, and questions — balancing gold-standard rigor with the practical realities of a fast-moving, scaled organization.
• Build partnerships with credible external validators, researchers, economists, evaluation firms, academic institutions, and research labs to strengthen public and donor confidence in ALG’s impact.
• Create a roadmap for when, where, and how ALG should pursue external validation, publish findings, commission independent evaluations, or subject its methodology to external review.
• Ensure external validation efforts are directly connected to organizational learning, fundraising, program improvement, and public trust, not research for research’s sake.

Build impact intelligence systems and data quality

• Partner with Data, Product, Engineering, Learning, Community, and Operations teams to embed impact measurement across the learner journey, from registration and baselines through program completion, transition into work, long-term outcomes, and alumni progression.
• Strengthen data pipelines and verification systems across surveys, platform data, CRM tools, employer feedback, relationship manager inputs, alumni updates, financial or KYC rails, LinkedIn/digital trace data, and other relevant sources.
• Build QA and governance systems that make impact data audit-ready, including audit trails, anomaly detection, dashboard health checks, data dictionaries, internal controls, documentation, and clear ownership for core metrics.
• Ensure dashboards and data products are reliable, donor-friendly, methodologically clear, and able to distinguish between actuals, estimates, projections, and externally validated outcomes.
• Work with technical teams to make impact data useful for decision-making, not just reporting, including predictive insights, segmentation, learner support interventions, and program improvement.

Turn evidence into learning, fundraising, and thought leadership

• Develop donor-facing and public-facing collateral that clearly explains ALG’s evidence standards, collection methods, verification layers, sampling approach, extrapolation logic, audit protocols, and methodological limitations.
• Partner with Fundraising and Partnerships to create credible impact assets for major donors, institutional funders, governments, employers, and strategic partners.
• Produce or oversee white papers, methodology briefs, board materials, impact reports, donor evidence packs, and thought leadership on ALG’s approach to economic mobility, AI-era workforce development, youth employment, entrepreneurship, household uplift, and durable career resilience.
• Lead a practical learning agenda that identifies the highest-value questions ALG must answer to improve outcomes, strengthen funder confidence, and scale responsibly.
• Translate impact data into actionable insights that improve learner experience, program design, community support, employer engagement, fundraising, and long-term outcomes.

Lead and evolve the Impact Team

• Lead and strengthen the Impact Team, building a culture that is rigorous, fast, transparent, ethical, analytical, and deeply connected to organizational strategy.
• Build the team’s capabilities across impact evaluation, data quality, analytics, survey design, storytelling, research partnerships, donor collateral, and product collaboration.
• Create operating rhythms that ensure the Impact Team is proactive, responsive, and embedded across the organization rather than functioning as a retrospective reporting unit.
• Serve as a senior advisor to leadership on impact claims, data risks, evidence quality, external validation, donor diligence, and public communication.
• Bring rigor without rigidity, structure without bureaucracy, and external credibility without slowing down ALG’s entrepreneurial pace.

Build the evidence and trust architecture

• Build the trust infrastructure for ALG’s next phase of scale: the methodologies, systems, validation partnerships, dashboards, governance, and public-facing evidence needed to make our impact claims credible under scrutiny.
• Develop and own ALG’s impact methodology, including approaches to data collection, verification, sampling, extrapolation, attribution, contribution, confidence intervals, error margins, data quality, and limitations
• Define the standards for what ALG can claim internally, what can be shared with donors, what requires caveats, and what is ready for external publication or independent validation.
• Move ALG’s impact narrative beyond short-term placement statistics to include income lift, economic mobility, promotions, entrepreneurship, household uplift, family support, resilience, and long-term career progression.
• Strengthen internal alignment around core impact definitions, metrics, data sources, reporting standards, and evidence thresholds, ensuring leadership, fundraising, product, and program teams are working from a single source of truth.

Lead rigorous evaluation and external validation

• Design and lead a rigorous research and evaluation agenda, including RCTs, quasi-experimental studies, tracer studies, longitudinal research, employer studies, learner surveys, and mixed-methods evaluation.
• Identify which research methods are appropriate for different programs, geographies, and questions — balancing gold-standard rigor with the practical realities of a fast-moving, scaled organization.
• Build partnerships with credible external validators, researchers, economists, evaluation firms, academic institutions, and research labs to strengthen public and donor confidence in ALG’s impact.
• Create a roadmap for when, where, and how ALG should pursue external validation, publish findings, commission independent evaluations, or subject its methodology to external review.
• Ensure external validation efforts are directly connected to organizational learning, fundraising, program improvement, and public trust, not research for research’s sake.

Build impact intelligence systems and data quality

• Partner with Data, Product, Engineering, Learning, Community, and Operations teams to embed impact measurement across the learner journey, from registration and baselines through program completion, transition into work, long-term outcomes, and alumni progression.
• Strengthen data pipelines and verification systems across surveys, platform data, CRM tools, employer feedback, relationship manager inputs, alumni updates, financial or KYC rails, LinkedIn/digital trace data, and other relevant sources.
• Build QA and governance systems that make impact data audit-ready, including audit trails, anomaly detection, dashboard health checks, data dictionaries, internal controls, documentation, and clear ownership for core metrics.
• Ensure dashboards and data products are reliable, donor-friendly, methodologically clear, and able to distinguish between actuals, estimates, projections, and externally validated outcomes.
• Work with technical teams to make impact data useful for decision-making, not just reporting, including predictive insights, segmentation, learner support interventions, and program improvement.

Turn evidence into learning, fundraising, and thought leadership

• Develop donor-facing and public-facing collateral that clearly explains ALG’s evidence standards, collection methods, verification layers, sampling approach, extrapolation logic, audit protocols, and methodological limitations.
• Partner with Fundraising and Partnerships to create credible impact assets for major donors, institutional funders, governments, employers, and strategic partners.
• Produce or oversee white papers, methodology briefs, board materials, impact reports, donor evidence packs, and thought leadership on ALG’s approach to economic mobility, AI-era workforce development, youth employment, entrepreneurship, household uplift, and durable career resilience.
• Lead a practical learning agenda that identifies the highest-value questions ALG must answer to improve outcomes, strengthen funder confidence, and scale responsibly.
• Translate impact data into actionable insights that improve learner experience, program design, community support, employer engagement, fundraising, and long-term outcomes.

Lead and evolve the Impact Team

• Lead and strengthen the Impact Team, building a culture that is rigorous, fast, transparent, ethical, analytical, and deeply connected to organizational strategy.
• Build the team’s capabilities across impact evaluation, data quality, analytics, survey design, storytelling, research partnerships, donor collateral, and product collaboration.
• Create operating rhythms that ensure the Impact Team is proactive, responsive, and embedded across the organization rather than functioning as a retrospective reporting unit.
• Serve as a senior advisor to leadership on impact claims, data risks, evidence quality, external validation, donor diligence, and public communication.
• Bring rigor without rigidity, structure without bureaucracy, and external credibility without slowing down ALG’s entrepreneurial pace.

Requirements

Skill Requirements - Essential

• 10+ years of relevant experience in impact evaluation, applied research, economics, workforce development, education outcomes, labor market analytics, social impact strategy, data science, or a related field.
• Deep expertise in rigorous impact methodology, including RCTs, quasi-experimental methods, causal inference, longitudinal studies, tracer studies, sampling, survey design, mixed-methods research, and evaluation design.
• Experience designing, managing, commissioning, or partnering on external evaluations with academic researchers, research organizations, foundations, multilaterals, or independent evaluators.
• Strong understanding of education-to-employment, workforce development, economic mobility, youth employment, entrepreneurship, income lift, household outcomes, or labor market transitions.
• Strong data fluency, including comfort working with dashboards, data pipelines, data warehouses, CRM systems, survey platforms, product analytics, and data quality processes.
• Ability to translate complex research and methodology into clear, credible materials for donors, boards, executives, governments, employers, and public audiences.
• Experience working cross-functionally with product, data, engineering, operations, learning, fundraising, communications, and senior leadership teams.
• Strong written communication skills, with the ability to produce methodology notes, donor briefs, board materials, impact reports, white papers, and thought leadership.
• Excellent judgment on evidence quality, including when to use gold-standard evaluation methods, when to use faster pragmatic approaches, and how to communicate uncertainty or limitations.
• Proven ability to lead teams, build systems, manage ambiguity, and operate effectively in fast-moving, entrepreneurial environments.
• Strong ethical grounding around data privacy, consent, responsible AI, equity, transparency, and the risks of overclaiming impact.
• A bias toward action, paired with the discipline to build systems that are credible, auditable, and trusted.

Skill Requirements - Essential

• 10+ years of relevant experience in impact evaluation, applied research, economics, workforce development, education outcomes, labor market analytics, social impact strategy, data science, or a related field.
• Deep expertise in rigorous impact methodology, including RCTs, quasi-experimental methods, causal inference, longitudinal studies, tracer studies, sampling, survey design, mixed-methods research, and evaluation design.
• Experience designing, managing, commissioning, or partnering on external evaluations with academic researchers, research organizations, foundations, multilaterals, or independent evaluators.
• Strong understanding of education-to-employment, workforce development, economic mobility, youth employment, entrepreneurship, income lift, household outcomes, or labor market transitions.
• Strong data fluency, including comfort working with dashboards, data pipelines, data warehouses, CRM systems, survey platforms, product analytics, and data quality processes.
• Ability to translate complex research and methodology into clear, credible materials for donors, boards, executives, governments, employers, and public audiences.
• Experience working cross-functionally with product, data, engineering, operations, learning, fundraising, communications, and senior leadership teams.
• Strong written communication skills, with the ability to produce methodology notes, donor briefs, board materials, impact reports, white papers, and thought leadership.
• Excellent judgment on evidence quality, including when to use gold-standard evaluation methods, when to use faster pragmatic approaches, and how to communicate uncertainty or limitations.
• Proven ability to lead teams, build systems, manage ambiguity, and operate effectively in fast-moving, entrepreneurial environments.
• Strong ethical grounding around data privacy, consent, responsible AI, equity, transparency, and the risks of overclaiming impact.
• A bias toward action, paired with the discipline to build systems that are credible, auditable, and trusted.