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Join us as Senior Data Modeller, where you will lead the delivery of advanced analytics, Business Intelligence (BI), Machine Learning (ML), and Generative AI solutions across the APAC region. You will design and deploy scalable, governed, and regulator-ready analytics solutions aligned to Barclays’ platform-led, product-oriented data strategy, while working closely with enterprise data, architecture, and governance teams.
Job Responsibility:
Lead the identification, design, and delivery of high-value analytics, BI, ML, and Generative AI use cases across investment banking, risk, regulatory, and operations domains
Design and deploy end-to-end analytics and ML pipelines, including feature engineering, model development, validation, deployment, and monitoring
Own the full ML lifecycle, ensuring explainability, validation, governance, and controlled change in line with enterprise standards
Deliver executive-grade BI dashboards and AI-driven insights for senior stakeholders
Design and implement Retrieval Augmented Generation (RAG) solutions within secure enterprise environments
Build reusable, governed analytics products aligned with enterprise data product standards
Collaborate with Data Architects and Engineers to design and validate conceptual, logical, and dimensional data models
Ensure compliance with Responsible AI, data governance, security, and regulatory frameworks
Provide technical leadership, mentorship, and stakeholder management across teams
Requirements:
Strong experience delivering advanced analytics, BI, ML, and AI solutions within financial services or investment banking
Proven end-to-end ownership of analytics and data science solutions from problem definition to business adoption
Hands-on expertise with modern analytics platforms (e.g., Databricks, Spark, Python, SQL)
Strong SQL skills and understanding of data modelling (conceptual, logical, dimensional)
Experience working in regulated environments with governance, controls, and explainability requirements
Experience collaborating with Data Architects, Data Modelers, and enterprise platform teams
Strong communication and stakeholder management skills
Nice to have:
Exposure to analytics engineering or DBT-based model-driven analytics
Experience with real-time or streaming data pipelines (e.g., Kafka)
Experience in regulatory, risk, or compliance-driven analytics initiatives
Familiarity with enterprise data product models and metadata-driven analytics ecosystems