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Based in the Group Customer Analytics & Decisioning team, you will be responsible for developing & optimizing Regulatory Compliance data pipelines & architecture. These will support analytical needs around topics such as Anti-Money Laundering, Know Your Customer and Investigations.
Create and maintain the optimal data pipeline architecture to enable ingestion from a wide variety of structured and unstructured data sources.
Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery and cleansing/transformation.
Support development and deployment of applications utilising the data pipelines to provide actionable insights into suspicious transactions, anomaly detection, network analysis and dashboarding .
Postgraduate degree in Statistics, Mathematics, Machine Learning or a related field
Minimum 7 years of working experience in data engineer, ETL, SAS/ML model or a related field
Strong hands-on skills in Statistics function, SQL & PL/SQL
Solid background in traditional structured database environments such as Teradata / Oracle
Knowledge on data warehouse and business process modelling solutions
Experience with developing business process analysis methodologies to evaluate, standardize, document, and implement improvements to business processes using modelling applications - using the likes of Python, SAS
Understanding of banking with exposure to Legal and Regulatory Compliance is preferred
Ideally some knowledge of analytical software tools such as Python / R / SAS / QlikView / Tableau / Spark
Energetic personality with an innovative, self-starting spirit. Someone that likes to ask "why ?"