Lead Data Scientist

To lead and scale Adani AI Labs' functional PODs, driving the strategic implementation of Generative AI and Data Science solutions across Projects, Procurement, Finance and HR.

This role is pivotal in transforming enterprise operations, optimizing resource allocation, and ensuring AI-driven decision-making aligns with the Adani Group's overarching digital transformation goals and massive industrial scale.

Qualifications

Educational Background

• Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, Data Science, or a related quantitative field.
• Certifications in Advanced AI/ML from recognized institutions or major cloud providers (e.g., AWS, Azure, GCP).

Required Qualifications & Experience

• 10-15 years of progressive experience in Data Science, Machine Learning, and Artificial Intelligence, with a proven track record of enterprise deployments.
• 10+ years in designing and implementing end-to-end data science and AI workflows at an enterprise scale.
• 5+ years in a leadership capacity, successfully managing cross-functional technical teams and aligning AI projects with business objectives.
• Extensive hands-on experience in leading Generative AI initiatives and managing large-scale AI functional pods or centers of excellence.
• Demonstrated success in delivering impactful AI solutions within projects, procurement, HR, or supply chain domains.Responsibilities
• Spearhead the development and expansion of AI functional PODs.
• Architect and deploy scalable Generative AI and machine learning models tailored to enterprise operational bottlenecks.
• Drive cross-functional collaboration to identify automation opportunities and embed AI capabilities into core business processes.
• Mentor and lead a high-performing team of data scientists and AI engineers, ensuring excellence in model development and deployment.
• Establish governance and best practices for AI development, ensuring ethical, secure, and robust solutions.
• Oversee the end-to-end lifecycle of AI projects, from conceptualization and prototyping to production and continuous monitoring.
• Partner with business stakeholders to translate complex operational challenges into data-driven, actionable AI strategies.
• Evaluate and integrate cutting-edge AI technologies and platforms to maintain Adani’s competitive edge in industrial digitization.Domain Expertise
• Deep functional knowledge of enterprise operations, particularly in Large Infra Projects, Procurement optimization and HR analytics.
• Mastery of state-of-the-art Generative AI frameworks (e.g., Domani SLMs, LLMs, RAG architectures, prompt engineering) and their enterprise applications.
• Strong understanding of data engineering pipelines, MLOps, and scalable cloud architectures for AI deployments.Non-Negotiable Requirements
• Expertise in Large Language Models (LLMs) & RAG: The candidate must possess deep, hands-on technical expertise in fine-tuning LLMs and building Retrieval-Augmented Generation architectures. Proficiency with platforms like Hugging Face, LangChain, Vertex AI, Enterprise Gemini and vector databases (e.g., Pinecone, Milvus) is essential for developing contextual AI solutions for Adani’s complex datasets.
• Proven Enterprise AI Leadership: Must have successfully led an AI/Data Science team through the full lifecycle of delivering scalable enterprise solutions. This requires not just technical acumen, but the ability to architect MLOps pipelines using tools like MLflow, Kubeflow, or cloud-native services (GCP/Azure) to ensure reliable deployments.
• Strategic Domain Integration: Must possess a strong ability to translate deep tech into business value, specifically within Projects, Procurement and HR domains. The candidate should be adept at utilizing advanced analytics/AI platforms (e.g., Databricks, Genie, Enterprise Gemini) to drive data-driven decision-making and operational transformation at a conglomerate scale.
• Digital & Operational Tools
• Proficiency in advanced AI/ML platforms and frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
• Expertise in cloud computing platforms relevant to AI deployment (e.g., Azure ML, Azure Databricks, and Google Vertex AI).
• Experience with enterprise resource planning (ERP) systems and data integration tools (e.g., SAP, Databricks, Snowflake).Preferred Skills
• Leadership Capabilities
• Proven ability to lead technological transformations and foster a culture of continuous innovation.
• Exceptional stakeholder management skills, capable of communicating complex AI concepts to non-technical executive leadership.
• Track record of building, mentoring, and retaining top-tier AI and data science talent.
• Strategic mindset with the capacity to align AI initiatives directly with measurable business ROI and operational efficiency.