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About the role
Were looking for a data-science leader who can turn raw data into clear insight and innovative AI products. You ll own projects end-to-end from framing business questions and exploring datasets to deploying and monitoring models in the cloud. Along the way you ll introduce generative-AI ideas such as chat assistants and retrieval-augmented search, steer a small team of data professionals, and work closely with product, engineering, and business stakeholders to deliver measurable value. Key Responsibilities Design and build predictive & forecasting models that drive measurable impact. Plan and run A/B experiments to validate ideas and guide product decisions. Develop and maintain data pipelines that ensure clean, trusted, and timely datasets. Lead generative-AI initiatives (e.g., LLM-powered chat, RAG search, custom embeddings). Package, deploy, and monitor models using modern MLOps practices in public cloud. Establish monitoring & alerting for accuracy, latency, drift, and cost. Mentor and coach the team, conducting code reviews and sharing best practices. Translate complex findings into clear, action-oriented stories for non-technical audiences. Ensure data governance and privacy across all projects, meeting internal and industry standards. Continuously evaluate new tools & methods, running quick PoCs to keep solutions cutting-edge. Core Skills & Experience Solid foundation in statistics, experiment design, and end-to-end ML workflows. Strong Python and SQL; proven record of moving models from notebook to production. Hands-on cloud experience (AWS, Azure, or GCP) with container-based deployment and CI/CD. Practical exposure to generative-AI projects prompt engineering, fine-tuning, or retrieval-augmented pipelines.
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