Mendria, "the Bloomberg Terminal for risk-adjusted real estate," is a climate–fintech, venture-backed company and has been nominated for the 2026 Earthshot Prize. Operating across major global financial centers, including New York, London, Paris, Amsterdam, Berlin, Singapore, and Tokyo, Mendria works with the world’s largest REITs, insurers, family offices, lenders, and institutional investors to detect and price the fastest-growing financial risks no model currently accounts for.Across 100+ assets modeled, Mendria’s interventions are estimated to prevent ~$900M in forecast climate-driven losses and abate 2.8 MtCO₂e annually, equivalent to removing 600,000 cars from the road. Our models help cities and institutions reduce up to ~35% of emissions per asset, all while improving ROI.Our founders have worked at BlackRock, Scale AI, Google, the UNEP, NOAA, DeepMedia AI, Netflix, and Paramount. We’re supported by 100+ environmental scientists and economists, including IPCC authors and Nobel Laureates.

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Focus: Mitigation or Adaptation

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We work with the world’s largest REITs, insurers, family offices, and institutional investors detect and price the fastest-growing financial risks no model accounts for.

We're growing Mendria’s founding team! Mendria is a venture-backed, climate–fintech company which been nominated for the 2026 Earthshot Prize. We help the world’s largest real estate owners and investment managers uncover and prevent hidden financial risks that traditional underwriting models miss. On the sustainability side, our models help cities and institutions reduce up to ~35% of emissions per asset and prevent ~40% of forecast climate-driven loss, all while improving ROI. Our founders have worked at BlackRock, Scale AI, Google, the UNEP, NOAA, DeepMedia AI, Netflix, and Paramount. We’re supported by 100+ environmental scientists and economists, including IPCC authors and Nobel Laureates.Job Description:Mendria processes millions of live data points to deliver fast, defensible underwriting at scale. The Backend Engineering team builds the distributed systems, APIs, and data infrastructure that power our modeling engine.Key Responsibilities:<ul><li>Build and maintain backend services that support data ingestion, model execution, and portfolio-scale processing.</li><li>Design clean, reliable APIs that expose underwriting intelligence to dashboards and enterprise clients.</li><li>Work across engineering and modeling teams to ensure fast, predictable, and reproducible computation.</li><li>Implement systems for data quality, job orchestration, and service observability.</li><li>Contribute to architectural decisions as the platform evolves to support larger institutional workloads.</li></ul>Education &amp; Qualifications (Preferred):<ul><li>Bachelor’s degree in computer science, engineering, or related field.</li><li>Strong programming skills in Python and experience with backend frameworks (FastAPI, Flask, Django).</li><li>Comfort working with SQL databases and designing scalable data pipelines.</li><li>Familiarity with cloud environments (AWS, GCP, or similar).</li><li>Clear problem-solving mindset, attention to detail, and pride in building reliable systems.</li><li>Ability to work in a fast, collaborative environment with high expectations for technical rigor.</li></ul>

Founding Backend Engineer

We're growing Mendria’s founding team! Mendria is a venture-backed, climate–fintech company that has been nominated for the 2026 Earthshot Prize. We help the world’s largest real estate owners and investment managers uncover and prevent hidden financial risks that traditional underwriting models miss. On the sustainability side, our models help cities and institutions reduce up to ~35% of emissions per asset and prevent ~40% of forecast climate-driven loss, all while improving ROI. Our founders have worked at BlackRock, Scale AI, Google, the UNEP, NOAA, DeepMedia AI, Netflix, and Paramount. We’re supported by 100+ environmental scientists and economists, including IPCC authors and Nobel Laureates.Job Description:The Data Science team develops the analytical and modeling foundations behind Mendria’s systems, fusing climate physics, financial engineering, stochastic modeling, and regulatory logic into a cohesive quant stack.Key Responsibilities:<ul><li>Develop and refine quantitative models that estimate risk, value, and ROI using diverse real-world data sources.</li><li>Analyze large, messy datasets to uncover patterns related to asset performance, loss drivers, and transition exposure.</li><li>Partner with engineering to translate analytical frameworks into scalable, production-grade systems.</li><li>Build scenario tools and sensitivity analyses to help clients understand financial outcomes under uncertainty.</li><li>Communicate complex findings clearly, concisely, and with commercial relevance for internal and external stakeholders.</li></ul>Education &amp; Qualifications (Preferred):<ul><li>Bachelor’s or advanced degree in statistics, computer science, engineering, applied math, economics, or a related quantitative field.</li><li>Strong analytical and statistical thinking, with experience working from first principles.</li><li>Demonstrated ability to work with data using Python (pandas, numpy, scikit-learn) and SQL.</li><li>Familiarity with cloud environments (AWS, GCP, or similar).</li><li>Comfort working with location-based or geospatial data is a plus.</li><li>Intellectual curiosity, comfort with uncertainty, and the ability to reason about financial implications from technical signals.</li><li>Clear communicator with the ability to translate quant insights into understandable recommendations.</li></ul>We review applications on a rolling basis and can move quickly for strong candidates.

Founding Data Scientist

We're growing Mendria’s founding team! Mendria is a venture-backed, climate–fintech company which has been nominated for the 2026 Earthshot Prize. We help the world’s largest real estate owners and investment managers uncover and prevent hidden financial risks that traditional underwriting models miss. On the sustainability side, our models help cities and institutions reduce up to ~35% of emissions per asset and prevent ~40% of forecast climate-driven loss, all while improving ROI. Our founders have worked at BlackRock, Scale AI, Google, the UNEP, NOAA, DeepMedia AI, Netflix, and Paramount. We’re supported by 100+ environmental scientists and economists, including IPCC authors and Nobel Laureates.Job Description: Mendria’s modeling stack powers underwriting for portfolios worth billions. The ML Systems Engineer builds and maintains the infrastructure that makes these models reliable, reproducible, and scalable. This role sits at the intersection of data science and backend engineering, ensuring every model, dataset, and output is versioned, validated, and production-ready.Key Responsibilities:<ul><li>Design and maintain systems for model training, versioning, and reproducibility.</li><li>Build pipelines that support large-scale batch scoring, sensitivity runs, and scenario generation.</li><li>Develop tools for model monitoring, drift detection, and performance validation.</li><li>Collaborate with Data Science, Backend, and Regulatory teams to bring new models into production smoothly.</li><li>Ensure clean data flow, structured assumptions, and audit-ready lineage across the modeling stack.</li></ul>Education &amp; Qualifications (Preferred):<ul><li>Bachelor’s degree in computer science, engineering, applied math, or related field.</li><li>Experience with ML infrastructure (MLflow, Airflow, containerization, CI/CD, experiment tracking).</li><li>Strong programming skills in Python; familiarity with scientific computing libraries.</li><li>Familiarity with cloud environments (AWS, GCP, or similar).</li><li>Comfort working with production data systems and distributed computing.</li><li>Comfort working with location-based or geospatial data is a plus.</li><li>Detail-oriented, rigorous, and motivated to build reliable modeling infrastructure from the ground up.</li></ul>

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