Fetcherr builds responsible AI that transforms market complexity into measurable profit growth. At the core of the company is the Market Model - a proprietary AI-powered model delivering accurate, granular demand predictions with 96% forecast accuracy and real-time decision intelligence for commercial teams. Built on a glass-box architecture, it uses market data - not personal data - with full transparency into logic and outcomes. First deployed in global aviation, the technology is industry-agnostic and scales across volatile markets. Fetcherr delivers a consistent average profit uplift of 7%, with corporate partners including Delta, Virgin Atlantic, WestJet, Viva, and Azul. We are seeking a talented and self-driven experienced **Data Scientist** to help advance our machine learning capabilities.This is a key role for someone passionate about leveraging machine learning to solve complex, real-world problems and deliver measurable business impact. Responsibilities: - Develop and implement state-of-the-art econometric and machine learning models for demand forecasting. - Conduct research and experimentation to evaluate novel approaches for improving accuracy, robustness, and scalability. - Collaborate with cross-functional teams (including product, data engineering, MLOPS and Platform) to deploy ML systems in production. - Clearly communicate complex technical findings to non-technical stakeholders, including product leaders and executives. **You’ll be a great fit if you have...** - 5+ years of hands-on experience in data science and machine learning with a proven record of leveraging modeling into business outcomes. - Proficiency in Python and its ML/data stack (e.g., PyTorch or TensorFlow, Pandas, NumPy, Scikit-learn). - Expertise in time-series forecasting, ideally Deep Learning based, preferably in demand prediction or related areas. - Feature engineering, feature importance testing, explainability based experience. - Master’s or PhD in Computer Science, Machine Learning, Statistics, Engineering or a relevant field. - Solid understanding of ML production workflows (versioning, testing, reproducibility, and deployment). - Excellent communication and collaboration skills. **Nice to have:** - Publications in top-tier, peer-reviewed ML/AI venues (e.g. ICLR, ICML, NIPS, etc.) - Experience applying ML in domains like finance, trading, revenue management etc. - Familiarity with cloud based solutions on GCP platform (e.g., Vertex AI, PubSub, Cloud Run Functions). - Strong data visualization and exploratory data analysis skills. - Familiarity with code optimization, containerization (e.g., Docker), CI/CD, or cloud-native architectures. - Participation in competitive programming or data science challenges (e.g., Kaggle). If you're excited about building impactful AI systems in a high-growth startup environment, and want to help redefine how industries price, forecast, and optimize, we’d love to hear from you.