Evaluation Specialist

Conservation X Labs Inc Evaluation Specialist Remote
· Contractor Company website Apply for Evaluation Specialist

CXL is seeking an Evaluation Specialist consultant to serve as the Fund's Experimental Design Lead. This Fund-level position is independent of all implementing partners and is responsible for the scientific integrity of the Fund's impact evaluation strategy.

Our mission is to prevent an impending sixth mass extinction – the first in Earth’s history driven by the actions of a single species: ours. Unlike traditional conservation efforts, Conservation X Labs focuses on leveraging the best technology, the newest innovation, interdisciplinary genius, and the power of the marketplace to boldly confront the biggest problems facing the planet. Though humans have driven this sixth extinction, we know humans have the power to reverse it.

Who We Are

Conservation X Labs (CXL) seeks to solve the world's greatest conservation problems by supporting innovative solutions that address the underlying drivers of extinction. We develop new technology, lead innovation competitions, and empower talented innovators across disciplines to create transformative products that serve people and our planet.

CXL is the operational lead for a new philanthropic Fund tackling fire — the leading cause of tropical primary forest loss — across three of South America's most globally significant ecoregions: the Amazon, the Pantanal, and the Chiquitania. The Fund brings together a diverse coalition of local, regional, and international partners to build and test integrated fire prevention and response systems, with the goal of learning quickly and scaling what works.

Interventions span community-led stewardship, technology and innovation, behavior change, accelerated ecological restoration, and financial mechanisms that incentivize fire-safe land management.

The Role

CXL is seeking an Evaluation Specialist consultant to serve as the Fund's Experimental Design Lead. This Fund-level position is independent of all implementing partners and is responsible for the scientific integrity of the Fund's impact evaluation strategy.

The Evaluation Specialist will validate the evaluation design, lead pre-registration of study protocols, oversee a quasi-experimental impact evaluation across multiple intervention geographies, and lead mixed-methods assessments at mid-term and close. Working closely with the Fund's M&E Expert Lead and scientific research partners, this consultant will ensure the Fund generates credible, publishable evidence about the impact of integrated fire management interventions at landscape scale.

The current program configuration spans multiple sites across three ecoregions and is designed as a rigorous exploratory phase: generating effect size estimates and site‑level variability data that will power a formally confirmatory study at full scale. The Evaluation Specialist will help frame and communicate this phased approach while maintaining the highest standards of scientific integrity.

This is a rare opportunity to shape the evaluation architecture of a first‑of‑its‑kind conservation fund — one that combines independent remote sensing, causal inference methods, and community‑level data to answer consequential questions about what works in fire management.

The Evaluation Specialist will lead the Fund's scientific evaluation strategy from pre‑registration through final evaluation, ensuring that causal inference methods are applied rigorously across a multi‑site, multi‑geography study design and that findings are credible to both the scientific and donor communities.

• Validate and finalize the experimental design
• Define and lock study site boundaries across all intervention and comparison geographies, in coordination with implementing partners and the M&E Expert Lead
• Pre‑register the evaluation design on an appropriate open science platform, including: research questions and hypotheses, study timeline, randomization approach where feasible, primary and secondary outcomes, statistical methods, covariates, missing data handling, minimum detectable effect sizes,…