Data Scientist [FILLED]

Postuler maintenant cyprien@darwindata.ai About Darwin We''re on a mission to revolutionize biodiversity impact assessment. Our cutting-edge platform helps businesses measure and manage their biodiversity footprint, integrating seamlessly into ESG compliance tools and carbon accounting platforms via API. The Opportunity With CSRD regulation now mandatory, we''re experiencing explosive demand. We''ve secured pre-seed funding and are working with leading consulting firms (Deloitte, KPMG, Carbone4, B&L Evolution, Utopies) and major organisations (Bouygues, Eurazeo). What''s next? We''re scaling our platform features and commercial reach throughout 2026-2027 to capture the regulatory wave. We''re investing >70% of our funding in tech to build Europe''s dominant biodiversity platform. The Team You''ll join a tight-knit data team working closely with engineering and science: Cyprien (CPTO) - Product, engineering & GTM Antoine (CSO) - Science & biodiversity expertise Pierre (Head of Data/AI) - Data pipelines, ML & infrastructure Igor (Backend) - API & Rust core (15+ years XP) Olivier (Frontend) - Vue.js app (20+ years XP) We move fast, own our work end-to-end, and ship features that directly impact enterprise clients. The Role As a Data Scientist, you''ll report directly to our Head of Data/AI and work at the intersection of ecological science and machine learning. You''ll develop models that power our biodiversity analytics and AI-driven insights. Your mission: Develop and deploy machine learning models for biodiversity impact assessment and risk quantification Build NLP and AI systems to extract insights from environmental data and enable conversational interfaces Design and implement statistical models to quantify nature-related financial risks Collaborate with our science team to translate ecological research into scalable algorithms Create data visualizations and analytics to communicate complex biodiversity metrics Continuously improve model accuracy, performance, and interpretability Example projects you could work on: Nature Stress Test - Build VaR-like models to quantify portfolio exposure to biodiversity-related shocks AI-powered insights - Develop NLP models for natural language querying of environmental data Biodiversity scoring - Create ML models to assess corporate nature footprint across supply chains Scenario modeling - Implement projection models using SSP/RCP scenarios and ecological forecasts What We''re Looking For Required: 3-5 years experience as a Data Scientist or ML Engineer Strong proficiency in Python (pandas, scikit-learn, PyTorch or TensorFlow) Experience with NLP and LLMs (fine-tuning, RAG, prompt engineering) Solid foundation in statistics and probability (hypothesis testing, regression, Bayesian methods) Experience deploying ML models to production Excellent communication skills to explain complex models to non-technical stakeholders Ownership mindset: you build it, you run it, you improve it Remote-friendly (CET timezone ±1h) Nice to have: Background in environmental science, ecology, or sustainability Experience with time series forecasting and geospatial data Knowledge of financial risk modeling (VaR, stress testing) Familiarity with Rust or willingness to learn B2B SaaS or enterprise data platform experience What We Offer Salary range: 50-65k€ depending on experience Founding equity package (ESOP): significant upside aligned with company growth Technical ownership: shape our AI and ML strategy from the ground up Direct collaboration with Head of Data/AI and CSO: bridge science and technology Remote flexibility with Paris office access if needed Mission-driven work: contribute to biodiversity preservation at scale Hiring Process Intro call (30 min) - Mutual fit, your background, your questions Technical interview (1h) - ML case study + modeling discussion Team fit (45 min) - Meet the team, culture & collaboration Offer Postuler maintenant cyprien@darwindata.ai