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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
