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Job Description

Role Summary :


Were looking for a data-science leader who can turn raw data into clear insight and innovative AI products. Youll own projects end-to-end - from framing business questions and exploring datasets to deploying and monitoring models in the cloud. Along the way youll 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, an 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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