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 (ME) 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 current 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.

Essentials

- Relevant professional background: 7-9 years of experience in ME, 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 diverse 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 programs 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.

Disclaimer: This job posting and location has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Evidence Lead, AI Access Initiative (EAII Advisors) (New Delhi)
🏢 Evidence Action
📍 New Delhi