Echo Labs - Chief Science Officer

Introduction

Echo Labs is building the scientific, and technical foundation for ecological intelligence: a multimodal system to measure, model, and forecast Ecosystem Condition as a dynamic property. We are a collaborative and interdisciplinary team of scientists and engineers engaged in a planetary moonshot – with a public good mission, operating like a start up.

We are a new Focused Research Organization (FRO) supported by Convergent Research and funded by the Advanced Research and Invention Agency to pursue high-risk, high-reward science in the public interest.

The Chief Science Officer (CSO) anchors this effort in scientific rigour, ecological credibility, and long-term legitimacy and plays a decisive role in ensuring that this infrastructure is scientifically sound and transformative.

The CSO is responsible for ensuring that Echo’s data, models, and interpretations faithfully reflect state-of-the‑art ecological science while enabling bold, operational innovation. This role bridges fundamental ecology, field methods, and applied modelling, translating ecological theory into scalable, decision-grade infrastructure.

This is a high-leverage role: you’ll lead Echo’s ecology vertical and relationship with the ecology community. The CSO reports to the CEO and works in close partnership with the Chief Technology Officer and Director of Product & Partnerships as a core member of Echo’s executive leadership team.

• Own and continuously refine Echo’s scientific framing of Ecosystem Condition, grounded in ECT+/SEEA typologies and current ecological theory.
• Ensure scientific defensibility, interpretability, and transparency of Echo’s outputs for the academic community, policymakers, and external partners.
• Set standards for scientific validation, benchmarking, and uncertainty characterisation across the programme.

• Lead the identification, evaluation, and strategic use of existing ecological and Earth-observation datasets, determining when external data can accelerate progress versus when new data generation is essential.
• Set the analytical direction for how existing datasets are integrated, stress-tested, or rejected, including defining appropriate benchmarks, comparators, and limitations.
• Guide early in-silico analyses to inform sampling design, modelling priorities, and go/no-go decisions, ensuring resources are focused on data and approaches with the highest scientific leverage.
• Establish criteria for reuse, interoperability, and alignment of legacy datasets with Echo’s Ecosystem Condition framework, avoiding dependence on datasets that are ecologically misaligned or methodologically brittle.

• Lead scientific oversight of Echo’s sampling architecture, ensuring ecological sensitivity and robustness.
• Guide methodological choices across in-situ data streams (eDNA, acoustics, vegetation structure, soil health, hydrology, etc.).
• Oversee ecological QA/QC, signal separability testing, and temporal sensitivity to disturbance and recovery.

• Work hand-in-hand with the CTO and ML leads to ensure ecological meaning is preserved in latent representations (“ecosystem fingerprints”) and predictive models.
• Validate that modelling choices align with ecological processes, scales, and constraints rather than spurious correlations.
• Champion explainability and ecological interpretability of model outputs.

• Act as Echo’s senior scientific representative to the ecological research community.
• Build trust and adoption through workshops, advisory engagement, and transparent publication of methods, data, and results.
• Shape Echo’s contribution to emerging standards in ecological monitoring, modelling, and data governance.
• Interface with the Science Advisory Board, translating feedback into operational scientific decisions.

• Established an internal scientific definition of Ecosystem Condition, aligned with ECT+/SEEA and explicitly scoped to what Echo will and will not measure.
• Audite…