About this role
Salary: £? - ? per year
Requirements: Strong Python programming skills, including data analysis using libraries such as PandasStrong understanding of machine learning, including both supervised and unsupervised techniquesExperience with tree-based and boosting algorithms such as XGBoost, LightGBM, and related approachesExperience working with large-scale datasets, ideally using PySparkStrong analytical and SQL skills for handling, querying, and interpreting complex datasetsAbility to communicate insights effectively through visualisations using tools such as Matplotlib, Plotly, or similarExposure to model interpretability techniques such as SHAP and LIMEPrevious experience within the Banking / Financial Services sectorFamiliarity with Financial Crime, AML, Compliance, or Transaction Monitoring domainsStrong data science and machine learning backgroundWillingness to learn the business context Responsibilities: Support a new initiative focused on Transaction Monitoring (TM) for Business BankingApply machine learning skills to real-world financial crime and transaction monitoring challengesHelp expand an existing machine learning-driven transaction monitoring capability from Retail Banking into Business Banking Technologies: SupportMachine LearningPythonPySparkSQLpandas More:
We are the Analytics Centre of Excellence and we are looking for an experienced ML Engineer to support a new initiative focused on Transaction Monitoring for Business Banking. This is a 6-month onsite role based in Glasgow, with Edinburgh also considered, requiring 2-3 days onsite. We are expanding an existing machine learning-driven transaction monitoring capability already underway within Retail Banking into the Business Banking space, and we are seeking someone who can bring strong technical capability and a willingness to learn the business context.
last updated 37 week of 2026