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.

Position Type: Permanent - Lead

Mode of Interview: Virtual

Experience: 15-22 Years

Work Mode: Hybrid

Skills: GenAI, autonomous agents, advanced NLP, machine learning and hands-on technical expertise

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Key responsibilities

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.

Role 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.

Data and AI Scientist