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Collegedunia - Data Science Lead - Generative AI

0 years

0 Lacs

Nagpur Maharashtra India

Posted:6 days ago| Platform: Linkedin logo

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Skills Required

data ai monitoring chat retrieval engineering design forecasting drive latency drift code governance statistics ml python sql aws azure gcp deployment tuning

Work Mode

On-site

Job Type

Full Time

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 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 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.
(ref:hirist.tech)

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