Key Responsibilities: • Deliver end-to-end data science solutions in a consultancy environment • Build and deploy custom forecasting models (e.g., time series, XGBoost, deep learning) • Implement reinforcement learning techniques for dynamic prediction • Apply causal inference and graph AI methods to uncover complex relationships • Develop and containerize models using Docker • Work within modern CI/CD pipelines to streamline deployment • Operate in a cloud environment (AWS preferred) • Contribute to the development of a data-driven web application using JavaScript/TypeScript and Next.js Required Skills & Experience: • Strong experience as a Full Stack Data Scientist • Deep expertise in time series forecasting and machine learning (XGBoost, deep learning, reinforcement learning) • Practical knowledge of Causal AI and Graph AI methodologies • Proficiency in Python for data science and model development • Experience with Docker, CI/CD workflows, and AWS • Comfortable working with JavaScript, Next.js, and ideally TypeScript • Ability to thrive in a consulting or agency environment with changing client demands • Strong ownership of delivery and adaptability to fast-moving projects Desirable: • Experience in retail analytics • Prior work in cross-functional teams building web-based data products • Exposure to start-up style or agile project settings