Senior Data Scientist – AI/ML & Generative AI

We are seeking a Senior Data Scientist to lead AI-driven initiatives delivering machine learning and Generative AI solutions within Capital Markets. This role focuses on building scalable models and applications for forecasting, anomaly/fraud detection, and LLM-based solutions (including RAG and agentic AI) on modern cloud platforms.

Key Responsibilities

Design, develop, and deploy machine learning models for forecasting, classification, and anomaly/fraud detection

Architect and implement Generative AI solutions, including RAG pipelines, prompt engineering, embeddings, and vector databases

Build scalable AI applications leveraging LLM APIs, orchestration frameworks, and agent-based systems

Develop modular, production-ready Python applications following robust software engineering practices (SOLID principles)

Deploy, monitor, and optimise models using MLOps practices on platforms such as Azure, AWS, and Databricks

Analyse large, complex datasets to derive actionable business insights

Collaborate with cross-functional teams and effectively communicate outcomes to technical and business stakeholders

Key Skills

Strong expertise in machine learning, statistical modelling, and data science techniques

Hands-on experience with Generative AI, including LLMs, RAG, prompt engineering, and vector databases

Practical experience with AI/LLM frameworks such as LangChain, LangGraph, CrewAI, AutoGen, or similar

Solid understanding of anomaly detection techniques (e.g. Autoencoders, XGBoost, Isolation Forest)

Proficiency in Python and SQL, with ability to develop complex, modular, and maintainable applications

Strong understanding of software engineering principles, including SOLID design principles

Experience with Databricks and cloud platforms (Azure Preferred)

Good understanding of Capital Markets domain and fraud detection use cases

Experience & Education

6+ years of experience in Data Science, Machine Learning, or AI-related roles

Bachelor’s degree required.

Attributes

Strong analytical thinking and problem-solving skills

Clear and effective communication with both technical and non-technical stakeholders

Delivery-focused with a pragmatic, cost-conscious mindset

Ability to work independently and collaboratively in cross-functional teams