Lead Data Scientist

Job Title: Lead Data Scientist – Generative AI (GenAI)

About Ganit

At Ganit, analytics is our playing field. We're not just data geeks—we're a family of scientists, refiners, and artisans. We manage data from the source and transform it into meaningful business insights, helping enterprises build state-of-the-art AI and analytics solutions that drive impactful decisions.

Founded in 2017, Ganit is a leading Data Science and Analytics consulting company with a team of 150+ passionate data scientists, analysts, and engineers. Our mission is to maximize decision velocity and minimize decision risk by enabling organizations to become truly data-driven.

At Ganit, innovation, collaboration, and continuous learning are at the core of everything we do.

Learn more at www.ganitinc.com

Position: Lead Data Scientist – Generative AI

Experience: 7–12 Years

Location: Bangalore / Mumbai / Chennai / Gurgaon

Role Overview

We are looking for a highly motivated Lead Data Scientist – Generative AI to lead the design, development, and deployment of enterprise-grade GenAI solutions. The ideal candidate will possess strong expertise in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, Prompt Engineering, and modern AI frameworks.

This role requires a blend of technical excellence, client-facing consulting experience, solution architecture capabilities, and team leadership. You will work closely with clients, business stakeholders, data engineers, and product teams to solve complex business problems using cutting-edge AI technologies.

Key Responsibilities

Client Consulting & Solution Design

• Engage with enterprise clients to understand business challenges and identify opportunities to leverage Generative AI.
• Translate business requirements into scalable AI solutions and technical architectures.
• Present AI strategies, solution approaches, and proof-of-concepts to senior stakeholders.

Generative AI Development

• Design, develop, and deploy production-ready GenAI applications.
• Build solutions using Large Language Models (OpenAI, Claude, Gemini, Llama, Mistral, etc.).
• Develop Retrieval-Augmented Generation (RAG) pipelines using vector databases.
• Implement AI Agents and multi-agent workflows using modern orchestration frameworks.
• Optimize prompts, context management, and model performance.

Machine Learning & Data Science

• Develop predictive models and ML solutions where traditional ML complements GenAI.
• Perform feature engineering, model evaluation, experimentation, and performance tuning.
• Apply statistical techniques to solve complex business problems.

Engineering & Deployment

• Build scalable AI services using Python and modern software engineering practices.
• Deploy AI models on cloud platforms such as AWS, Azure, or GCP.
• Develop APIs and integrate AI capabilities into enterprise applications.
• Monitor model performance, cost optimization, and production reliability.

Collaboration

• Partner with Product Managers, Solution Architects, Data Engineers, and Software Engineers to deliver end-to-end AI solutions.
• Collaborate with cross-functional teams throughout the project lifecycle.

Leadership & Mentorship

• Lead and mentor a team of Data Scientists and AI Engineers.
• Conduct technical reviews and establish best practices.
• Guide junior team members in model development, experimentation, and deployment.

Research & Innovation

• Stay current with advancements in LLMs, multimodal AI, Agentic AI, and emerging GenAI technologies.
• Evaluate new models, frameworks, and open-source tools.
• Drive innovation through internal accelerators, reusable assets, and thought leadership.

Preferred Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field.
• 8–12 years of experience in Data Science or Machine Learning.
• 2+ years of hands-on experience building production-grade Generative AI applications.
• Experience in consulting or client-facing roles.
• Strong communication and stakeholder management skills.
• Experience leading technical teams and mentoring data scientists.