Lloyds Banking Group

Lead Data and AI Scientist

Lloyds Banking Group Hyderabad, Telangana, India

Financial Services · 10,001+ employees

Yesterday
Principal (10+ yrs) Full-time India
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About the role

The lead Data & AI Scientist will architect and scale AI/ML solutions, including GenAI and autonomous agents, to solve complex business problems. They will also mentor junior team members and establish best practices for model development, deployment, and governance.

What they look for

Data Science Artificial Intelligence Machine Learning GenAI NLP Python LangChain LangGraph LLMs Statistics Deep Learning MLOps AIOps Cloud Computing Containerization Data Governance

Requirements

Candidates must have over 18 years of experience with a strong foundation in statistics, machine learning, and deep learning. Proficiency in GenAI frameworks, NLP, and MLOps practices is required, with an advanced degree preferred.

Benefits

Flexible working

Full description

End Date

Sunday 30 August 2026

We Support Flexible Working – Click here for more information on flexible working options

Flexible Working Options

Hybrid Working

Job Description Summary

Job Family: Data Science & AI > Data & AI Scientists Business Title: Data Science & AI Engineering Lead Grade: F Location: Hyderabad, Lloyds Technology Center Department: AI Centre of Excellence (CDAO) YOE: 18+ Years

Role Overview We are 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 our AI/ML initiatives, mentoring talent, and delivering high-impact outcomes through cutting-edge technologies including GenAI, autonomous agents, advanced NLP, and machine learning.

Job Description

Role Overview

We are 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 our AI/ML initiatives, mentoring talent, and delivering high-impact outcomes through cutting-edge technologies including GenAI, autonomous agents, advanced NLP, and machine learning.

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, optimising 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 and improve delivery processes, resource allocation, and prioritisation frameworks.
  • Establish best practices for model development, deployment, monitoring, and governance.

Required Skills & Experience

  • 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/customisation techniques.
  • Ability to design and implement autonomous AI agents capable of observation, planning, reasoning, and action.
  • Proficiency in analysing large datasets to identify trends, model improvements, and optimisation opportunities.
  • Familiarity with MLOps/AIOps practices and tools for scalable model deployment and lifecycle management.

Preferred Qualifications

  • Advanced degree (MSc/PhD) in Computer Science, Data Science, AI/ML, or related field.
  • Experience in cloud platforms (Azure, AWS, GCP) and containerisation (Docker, Kubernetes).
  • Knowledge of enterprise AI governance, ethical AI, and model interpretability.