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Onactive Consulting
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Data Scientist (Generative AI) Lead

Data Scientist (Generative AI) Lead

Onactive Consulting

4 - 6 years

6 - 8 Lacs

Nagpur

Posted:9 hours ago| Platform:

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Skills Required

Product engineering data science GCP Cloud data governance Deployment Forecasting AWS SQL Python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Job role Data Scientist (Generative AI) Lead

Experience: 4 6 years | Location: Nagpur

Role Summary:

We re 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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Data Scientist (Generative AI) Lead