Kubelt
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. About this role 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. Core Responsibilities Conceptual Framework: 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. Data Strategy and Analytical Direction: 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. Ecological Data Generation: 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. Modelling Integration and Ecological Interpretability: 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. Scientific Leadership, Governance and External Engagement: 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. Progression. In six months you will have Established an internal scientific definition of Ecosystem Condition, aligned with ECT+/SEEA and explicitly scoped to what Echo will and will not measure. Audited existing ecological data to identify usable signals, inferable dynamics, and critical gaps, guiding early go/no-go decisions on new data collection. Set clear priorities for early models and metrics, focusing on a small number of high-leverage downstream tasks rather than solving everything at once. Designed an initial metric and model architecture, including decisions on single vs. multi-layer representations and a strategy for ecological interpretability. Led internal and external scientific workshops to align sampling, modelling, and core scientific questions, resulting in shared buy-in and a v1 sampling design. Produced foundational scientific artifacts, including a v1 Ecosystem Condition framework, data-to-signal mapping, interpretability plan, and a scientific risk register. We Offer (Amazing Benefits) A rare chance to build institutional architecture for frontier science and work with some of the smartest and most talented experts from different fields. Up to a 6% employer pension contribution, with optional additional salary sacrifice, because future-you deserves comfort. Top-tier private medical and dental insurance-are fully covered for you and your dependents. Stay healthy, my friend. Generous parental leave-20 weeks make-whole-pay for both parents. 25 days of holiday allowance. Wellness allowance for fitness and wellness activities. Profile (You Are) PhD (or equivalent) in ecology, ecosystem science, environmental science, or a closely related field. Deep understanding of ecosystem functioning, resilience, or biodiversity dynamics, ideally across multiple spatial scales. Familiarity with ecological modelling, including interaction with machine learning. Strong basis in advanced statistical methods. Proven background in rigorous experimental design. Demonstrated experience designing, interpreting, or overseeing field-based ecological data collection. Track record of interdisciplinary collaboration across ecology, data science, and engineering. Exceptional scientific judgement and communication skills, with the ability to translate complexity into clarity. Highly organised and outcome-focused, with experience structuring workplans, prioritising trade-offs, and driving progress across interdisciplinary teams under time and resource constraints. Highly Valued Experience Experience working with multimodal ecological datasets (e.g. combining field data with Earth observation). Prior involvement in large-scale or national ecological monitoring programmes. Experience engaging with policy, regulatory, or applied decision-making contexts. Familiarity with FAIR + CARE data principles or ecological data governance. Leadership roles in collaborative or mission-driven research initiatives. Demonstrated ability to translate scientific vision into delivered products or platforms, with experience taking complex research programmes from concept through execution against clear timelines and milestones. Track record of operating in delivery-oriented environments (e.g. research infrastructure builds, applied science programmes, or mission-driven organisations) where scientific ambition is matched with disciplined execution. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 100000 - 130000 GBP a year Title commensurate with experience: CSO / Director of Ecological research Bonus: Performance-based
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. About this role 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. Core Responsibilities Conceptual Framework: 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. Data Strategy and Analytical Direction: 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. Ecological Data Generation: 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. Modelling Integration and Ecological Interpretability: 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. Scientific Leadership, Governance and External Engagement: 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. Progression. In six months you will have Established an internal scientific definition of Ecosystem Condition, aligned with ECT+/SEEA and explicitly scoped to what Echo will and will not measure. Audited existing ecological data to identify usable signals, inferable dynamics, and critical gaps, guiding early go/no-go decisions on new data collection. Set clear priorities for early models and metrics, focusing on a small number of high-leverage downstream tasks rather than solving everything at once. Designed an initial metric and model architecture, including decisions on single vs. multi-layer representations and a strategy for ecological interpretability. Led internal and external scientific workshops to align sampling, modelling, and core scientific questions, resulting in shared buy-in and a v1 sampling design. Produced foundational scientific artifacts, including a v1 Ecosystem Condition framework, data-to-signal mapping, interpretability plan, and a scientific risk register. We Offer (Amazing Benefits) A rare chance to build institutional architecture for frontier science and work with some of the smartest and most talented experts from different fields. Up to a 6% employer pension contribution, with optional additional salary sacrifice, because future-you deserves comfort. Top-tier private medical and dental insurance-are fully covered for you and your dependents. Stay healthy, my friend. Generous parental leave-20 weeks make-whole-pay for both parents. 25 days of holiday allowance. Wellness allowance for fitness and wellness activities. Profile (You Are) PhD (or equivalent) in ecology, ecosystem science, environmental science, or a closely related field. Deep understanding of ecosystem functioning, resilience, or biodiversity dynamics, ideally across multiple spatial scales. Familiarity with ecological modelling, including interaction with machine learning. Strong basis in advanced statistical methods. Proven background in rigorous experimental design. Demonstrated experience designing, interpreting, or overseeing field-based ecological data collection. Track record of interdisciplinary collaboration across ecology, data science, and engineering. Exceptional scientific judgement and communication skills, with the ability to translate complexity into clarity. Highly organised and outcome-focused, with experience structuring workplans, prioritising trade-offs, and driving progress across interdisciplinary teams under time and resource constraints. Highly Valued Experience Experience working with multimodal ecological datasets (e.g. combining field data with Earth observation). Prior involvement in large-scale or national ecological monitoring programmes. Experience engaging with policy, regulatory, or applied decision-making contexts. Familiarity with FAIR + CARE data principles or ecological data governance. Leadership roles in collaborative or mission-driven research initiatives. Demonstrated ability to translate scientific vision into delivered products or platforms, with experience taking complex research programmes from concept through execution against clear timelines and milestones. Track record of operating in delivery-oriented environments (e.g. research infrastructure builds, applied science programmes, or mission-driven organisations) where scientific ambition is matched with disciplined execution. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 100000 - 130000 GBP a year Title commensurate with experience: CSO / Director of Ecological research Bonus: Performance-based
Kubelt
Introduction Echo Labs is building a 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. About this role Echo Labs is seeking a Director of Modelling to design and build the data pipelines and modelling infrastructure that translate raw ecological signals into testable models of ecosystem condition. You will help turn ecological hypotheses into experiments, experiments into validated models, and validated models into decision-grade outputs. As we explore what is possible with new measures and representations of ecosystem state, you will be responsible for evaluating progress. You will help define success in a system that is complex to model using results that are challenging to interpret. This role reports to the Chief Technology Officer and works in close partnership with the Chief Science Officer. This is a rare opportunity to architect the conceptual and technical frameworks that define how ecosystems are measured and modelled. Core Responsibilities Experiment design & strategy: Design experiments that isolate signal from noise in ecological data, and design tests that can increment progress forward when results are ambiguous. Work with the CTO to prioritize intermediate outputs, publication opportunities, and risks. Work iteratively with the CSO to test and refine modelling approaches and uncertainty quantification that can be interpreted in ecological context. Define a standardization strategy that ensures model comparability across ecosystems and geographies. Research execution: Translate ecological hypotheses from the CSO into testable ML experiments. Implement, train, and evaluate models that characterise ecosystem condition across multiple measurement modalities. This will range from implementing classic machine learning to fine-tuning modern deep learning models. Contribute to research outputs: white papers, technical documentation, and peer-reviewed publications. Maintain infrastructure: Working with a growing team under your management, you will develop and maintain the technical stack to ensure reproducible, rapid experimentation. Team and growth: Work with the leadership team to hire and lead additional engineers and data scientists. Evaluate and communicate needs and opportunities to creatively accelerate progress. Establish technical standards, code review practices, and documentation norms. Profile (You Have) 8+ years in machine learning, data engineering, or applied research with end-to-end system ownership. Track record with machine learning infrastructure and experiment tracking, model versioning, reproducible pipelines. Experience with multimodal data. At minimum two of time-series sensor data, audio/acoustic data, imagery, or geospatial/remote sensing. Experience with cloud platforms (AWS or GCP) and MLOps tooling. Demonstrated ability to scope problems, make architectural decisions, and deliver without close supervision. Strong scientific communication. You have the ability to explain technical choices across domains and document work for reproducibility. Highly Valued Experience Background in ecology, environmental science, Earth observation, or prior work with ecological datasets. Prior work with bioacoustic data, eDNA, or biodiversity monitoring systems. Experience hiring and managing technical teams at early-stage organizations. Contributions to open-source ML or scientific software projects. Progression In the first six months, you'll help deliver an architecture for Echo's modeling platform. Core data pipelines will be operational using previously-generated datasets. First experiments are running to explore how ecosystem condition can be characterized across dimensions of ecosystem condition defined in conjunction with the CSO and integrating feedback from expert workshops. Initial technical documentation and reproducibility standards in place. You have an idea of what first major research outputs (white papers or publications) will be and how to communicate them. Hiring plan for technical team defined. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 145000 - 168000 GBP a year Title commensurate with experience: Senior Director / Chief Technology Officer possible. Bonus: Performance-based
Introduction Echo Labs is building a 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. About this role Echo Labs is seeking a Director of Modelling to design and build the data pipelines and modelling infrastructure that translate raw ecological signals into testable models of ecosystem condition. You will help turn ecological hypotheses into experiments, experiments into validated models, and validated models into decision-grade outputs. As we explore what is possible with new measures and representations of ecosystem state, you will be responsible for evaluating progress. You will help define success in a system that is complex to model using results that are challenging to interpret. This role reports to the Chief Technology Officer and works in close partnership with the Chief Science Officer. This is a rare opportunity to architect the conceptual and technical frameworks that define how ecosystems are measured and modelled. Core Responsibilities Experiment design & strategy: Design experiments that isolate signal from noise in ecological data, and design tests that can increment progress forward when results are ambiguous. Work with the CTO to prioritize intermediate outputs, publication opportunities, and risks. Work iteratively with the CSO to test and refine modelling approaches and uncertainty quantification that can be interpreted in ecological context. Define a standardization strategy that ensures model comparability across ecosystems and geographies. Research execution: Translate ecological hypotheses from the CSO into testable ML experiments. Implement, train, and evaluate models that characterise ecosystem condition across multiple measurement modalities. This will range from implementing classic machine learning to fine-tuning modern deep learning models. Contribute to research outputs: white papers, technical documentation, and peer-reviewed publications. Maintain infrastructure: Working with a growing team under your management, you will develop and maintain the technical stack to ensure reproducible, rapid experimentation. Team and growth: Work with the leadership team to hire and lead additional engineers and data scientists. Evaluate and communicate needs and opportunities to creatively accelerate progress. Establish technical standards, code review practices, and documentation norms. Profile (You Have) 8+ years in machine learning, data engineering, or applied research with end-to-end system ownership. Track record with machine learning infrastructure and experiment tracking, model versioning, reproducible pipelines. Experience with multimodal data. At minimum two of time-series sensor data, audio/acoustic data, imagery, or geospatial/remote sensing. Experience with cloud platforms (AWS or GCP) and MLOps tooling. Demonstrated ability to scope problems, make architectural decisions, and deliver without close supervision. Strong scientific communication. You have the ability to explain technical choices across domains and document work for reproducibility. Highly Valued Experience Background in ecology, environmental science, Earth observation, or prior work with ecological datasets. Prior work with bioacoustic data, eDNA, or biodiversity monitoring systems. Experience hiring and managing technical teams at early-stage organizations. Contributions to open-source ML or scientific software projects. Progression In the first six months, you'll help deliver an architecture for Echo's modeling platform. Core data pipelines will be operational using previously-generated datasets. First experiments are running to explore how ecosystem condition can be characterized across dimensions of ecosystem condition defined in conjunction with the CSO and integrating feedback from expert workshops. Initial technical documentation and reproducibility standards in place. You have an idea of what first major research outputs (white papers or publications) will be and how to communicate them. Hiring plan for technical team defined. Outro We're bringing together top talent from academia, industry, and startups to build a new model for innovative R&D. We are committed to creating an inclusive and diverse workplace where everyone has the opportunity to thrive. We believe in hiring individuals based on their unique talents-not on race, color, religion, ethnicity, gender, gender identity, sexual orientation, disability, age, military or veteran status, or any other characteristic protected by law or our company policies. We are more than a proud Equal Employment Opportunity employer. Our goal is to foster a healthy, safe, and respectful environment where all employees are valued and treated with dignity. 145000 - 168000 GBP a year Title commensurate with experience: Senior Director / Chief Technology Officer possible. Bonus: Performance-based