Job Description :

Our client is a leading financial services organisation seeking a hands-on Lead Data & AI Scientist to drive the development and scaling of AI-powered solutions across the enterprise. This role is pivotal in shaping the technical direction of the organization's AI/ML initiatives, mentoring talent, and delivering high-impact outcomes.

The position requires deep expertise across GenAI, autonomous agents, advanced NLP and machine learning, along with the ability to architect and scale enterprise-grade AI/ML solutions and lead cross-functional delivery.

Technical Leadership & Strategy :

- Lead the design, incubation, and scaling of AI/ML solutions that solve complex business problems.

- Architect and implement GenAI-powered systems, including Retrieval-Augmented Generation (RAG) pipelines and autonomous agents.

- Evaluate and integrate open-source and proprietary LLMs, optimizing for performance and business value.

Solution Delivery :

- Translate business requirements into robust, scalable AI/ML solutions.

- Collaborate with cross-functional teams to ensure seamless integration of AI capabilities into products and platforms.

- Drive experimentation, rapid prototyping, and iterative development.

Team Development & Mentorship :

- Guide and mentor data scientists, ML engineers, and junior developers.

- Foster a culture of technical excellence, innovation, and continuous learning.

Operational Excellence :

- Partner with CoE leaders to participate in and improve delivery processes, resource allocation, and prioritization frameworks.

- Establish best practices for model development, deployment, monitoring, and governance.

Eligibility Requirements :

- Experience : 15 - 22 years

- Strong foundation in statistics, machine learning, and deep learning.

- Proven experience in building and deploying GenAI solutions using frameworks like LangChain, LangGraph, or similar.

- Expertise in Natural Language Processing (NLP), including semantic search, entity recognition, and text generation.

- Hands-on experience with LLMs (e.g., GPT, LLaMA, Claude, Mistral) and fine-tuning/customization techniques.

- Ability to design and implement autonomous AI agents capable of observation, planning, reasoning, and action.

- Proficiency in analyzing large datasets to identify trends, model improvements, and optimization opportunities.

- Familiarity with MLOps/AIOps practices and tools for scalable model deployment and lifecycle management.

- Advanced degree (MSc/PhD) in Computer Science, Data Science, AI/ML, or related field preferred.

- Experience in cloud platforms (Azure, AWS, GCP) and containerization (Docker, Kubernetes) preferred.

- Knowledge of enterprise AI governance, ethical AI, and model interpretability preferred.