Live opening · Posted 7 days ago

Evidence Lead, AI Access Initiative (EAII Advisors)

Evidence Action · New Delhi, Delhi, India
Workable No
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Posted 7 days ago
CompanyEvidence Action
LocationNew Delhi, Delhi, India
Work modeNo
SourceWorkable
Listed7 days ago

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About the role

Description supplied by the original job listing.

About The AI Access Initiative (2AI)
We're at an inflection point in artificial intelligence – presenting both tremendous potential opportunity and risk for people in developing countries. AI capabilities are improving on a timescale measured in months, while development systems often move on timescales measured in decades. Much of the technology needed for positive impact exists today, but few organizations exist to bridge research, deployment, and scaled implementation: we must act now to ensure AI's benefits reach people in poverty in LMICs.
Incubated at Evidence Action, we're scaling The AI Access Initiative, an organization focused on scaling AI-enabled 'big bets' to benefit tens or hundreds of millions of people in poverty in low- and middle-income countries (LMICs). We operate at the intersection of global development actors, top AI labs, and leading researchers to drive meaningful access to AI's benefits for the 3.5 billion people living in poverty globally. We create "public good," open-sourced playbooks, toolkits, and insights that define how to design and launch tractable and impactful AI-enabled programs. Given the scale of opportunity, we expect our portfolio to expand substantially, but to start, we're scaling two programs focused on AI in Agriculture and AI in Health.
Agriculture: We have an ambitious goal to reach 100M+ farmers with AI-enabled weather forecasts, expand forecast R&D to generate novel forecasts, and build public and private sector (WhatsApp, telcos) delivery channels to deliver new, LLM-generated voice and image content that maximizes behavior change.
Health: Here, our initial goal is to scale AI-enabled clinical decision support to 20M+ people via telemedicine platforms, dramatically improving diagnosis and health outcomes at a national level. We are also planning to explore and test novel interventions for low-resource settings, including direct-to-consumer (DTC) health interventions.
We are led by former Evidence Action CEO Kanika Bahl, a founding member of Anthropic's Long-Term Benefit Trust, and advised by Nobel Laureate Michael Kremer; Dario Amodei, CEO of Anthropic; and Kent Walker, President, Global Affairs for Alphabet and Google. This work builds on Evidence Action's track record reaching 530M+ people with cost-effective, evidence-based programs across 9 countries in Africa and Asia, with a focus on last-mile delivery.
About 2AI India and EAII Advisors
EAII Advisors, Evidence Action's technical partner in India, supports state governments in delivering evidence-based public health programs. Operating across 10 states, EAII Advisors provides technical assistance to ministries of health, education, water, and women and child development, reducing health burdens in impoverished communities and improving the long-term wellbeing of children and families.
2AI India is being incubated as a project within EAII Advisors, with plans to spin off into an independent entity at the end of this year. We are hiring a founding team: the first hires will shape the culture, establish the operating model, and own early wins before the organization scales.
Roles and Responsibilities
The Evidence Lead is 2AI India's primary engine for measuring whether our programs work and why. This is not a traditional monitoring and evaluation (M&E) role. The focus is generating insights that change program design in real time. Data collection for government reporting is a real but secondary function, roughly 20% of the role. The Evidence Lead is also expected to be actively applying AI and machine learning (ML) tools to evaluation.
Evidence Generation and Program Measurement
Measures the effectiveness of new programs and ideas, from early concept tests through scaled delivery, and defines what "working" means for each before it launches.
Identifies the right data sources for evaluation, including administrative data, program data, partner data, and primary collection, and making the tradeoffs between rigor, cost, and speed explicit.
Designs and runs cost-effectiveness models, making the assumptions behind each result legible to the people making the call.
Builds the measurement and feedback loops into program design from the start rather than retrofitting them after launch.
Owns the data collection and reporting obligations that come with government partnerships, roughly 20% of the role,
Thought Partnership to Programs
Serves as a thought partner to the programs team on program design, ensuring programs are built to be measurable and monitoring and evaluation efforts measure what really matters.
Translates findings into recommendations that program leads can act on, and is explicit about the confidence behind each one.
AI and ML Applied to Evaluation
Applies AI and ML tools directly to evaluation and data analysis work, and keeps that practice current as the tools change.
Builds the data and modeling infrastructure that lets a small team run rapid and purpose-built analysis.
External Representation
Presents 2AI's evidence and data externally, with findings tailored to the needs of specific audiences: funders, partners, government counterparts, and the research community.
Team building and enablement
Fosters a strong, values-aligned culture as a leader across the organization.
Willingness to roll-up sleeves and pitch in to the organization building activities required of a founding team.
Overtime, hires and enables a team of strong monitoring, learning, and evaluation professionals committed to objectively assessing our programs and fostering their improvement.
Disclaimer: The duties and responsibilities described are not a comprehensive list and additional tasks may be assigned to the employee from time to time.
Requirements
Essentials:
Relevant professional background: 7-9 years of experience in M&E, impact evaluation, or applied research in global health or international development
Rigorous evidence environment: has worked in an organization where methodological standards were high and contested, such as academic research, a think tank, or an equivalent research lab
Applied AI and ML fluency: is already using AI and ML tools in evaluation and data analysis work today
Cost-effectiveness modelling: experience building and updating cost-effectiveness analyses, and can explain the assumptions driving a result to a non-technical decision-maker
Analytical structuring: structures ambiguous problems, thinks analytically, and solves quantitative problems without waiting for a fully specified brief
Program collaboration instincts: experience working in close proximity to programs; can understand how program needs and constraints differ from research needs, and adjusts the evidence agenda accordingly
Clear communication: shows clarity of thought, writes compellingly, and translates technical information into common language for varied audiences
External credibility: can present to funders, government counterparts, and technical peers and hold up under questioning
Experience navigating Indian government data systems and state-level reporting requirements
Comfort with ambiguity: a track record of doing well in early-stage, resource-constrained environments where the path is not defined and you build it as you go
Initiative and bias to action: takes ownership of unassigned problems and moves without being asked
What Success Looks Like
In the First 6 Months:
You have a working measurement approach with key indicators for the agriculture program, agreed with the Program Director, that specifies what evidence would change the program's direction.
You have built or adapted a cost-effectiveness model for at least one priority intervention, and leadership understands and trusts its assumptions.
You have mapped the available data landscape in India, including what government and partner systems can and cannot tell us.
Compensation : Competitive and commensurate with the individual's credentials, experience, and previous pay scale.
Benefits
EAII provides a comprehensive benefits package for employees. Benefits include:
Comprehensive health insurance with IPD and OPD provisions
Life and Accidental insurance
PF, ESIC and Gratuity as per statutory requirements
Generous leave
Mental and physical wellbeing benefits
Learning & Development benefits
Avenues for engagement and recognition
Note: This role will be open for applications until October 09,2026 . Please apply at your earliest convenience. We may close this search earlier than the specified date if we find the right fit. Due to the volume of applications received, we will only be able to contact shortlisted candidates.

Work arrangement
No

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