Lead Data Scientist

Overview

• Lead Data Scientist - Financial Services, Abu Dhabi
• Discover the Opportunity
• We’re partnering with a leading financial services organisation in Abu Dhabi that is continuing to scale its advanced analytics and AI capabilities.
• This role sits within a high-impact AI and product analytics team, focused on delivering production-grade machine learning solutions that drive data-led decision-making across the business.
• You will play a key role in translating complex business challenges into scalable data science solutions, working closely with product, engineering, and architecture teams to deliver real-world impact.
• This is a highly hands-on position suited to a technically strong data scientist who enjoys owning the full lifecycle of AI use cases while contributing to best practices across modelling, experimentation, and MLOps.
• Discover the Responsibilities
• Translate complex business problems into structured analytical and machine learning solutions, defining hypotheses, success metrics, and validation strategies
• Lead the design and development of advanced statistical, machine learning, and NLP models to solve high-impact use cases
• Own the end-to-end data science lifecycle, including data exploration, feature engineering, model development, validation, and deployment
• Conduct rigorous experimentation using cross-validation, back-testing, and statistical analysis to continuously improve model performance
• Collaborate with data engineering teams to ensure high-quality, scalable data pipelines and curated datasets for production use
• Support model deployment using APIs, batch, or streaming approaches, ensuring scalability, performance, and security
• Monitor model performance, data drift, and reliability, implementing retraining strategies and lifecycle management processes
• Ensure models meet interpretability, fairness, and regulatory standards within a governed environment
• Contribute to code quality, reusability, documentation standards, and continuous improvement of team practices
• Support model governance, documentation, and audit readiness, ensuring compliance with internal and regulatory frameworks
• Discover the Requirements
• 8+ years of experience delivering end-to-end data science and machine learning solutions in production environments
• Strong hands-on expertise in Python (e.g. pandas, NumPy) and SQL, with experience writing clean, production-ready code
• Strong foundation in statistics, experimentation, and analytical techniques, including hypothesis testing and A/B testing
• Experience with supervised and unsupervised machine learning, feature engineering, model selection, and performance optimisation
• Experience working with large datasets, including data preparation, EDA, and insight generation
• Experience deploying and maintaining models in production, including monitoring, retraining, and lifecycle management
• Strong understanding of MLOps practices and working within CI/CD-driven environments
• Experience working in regulated or data-governed environments is highly preferred
• Strong stakeholder management skills, with the ability to communicate complex insights to both technical and non-technical audiences
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field