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
