paced, cross-functional teams to deliver data-driven solutions iterative * Familiarity with SQL and experience in working with relational databases. * Knowledge of data pre-processing techniques, feature engineering, and model evaluation metrics. This is an excellent opportunity on a great project of work, If you are looking for your next exciting opportunity, apply now for your CV to reach More ❯
the global/mandate processes are secured * Support Operations in complex and high impact issues and problems as they arise. * Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products * Support product managers on lifecycle management More ❯
the global/mandate processes are secured * Support Operations in complex and high impact issues and problems as they arise. * Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products * Support product managers on lifecycle management More ❯
fit for purpose and satisfies the regulatory criteria for the winding down of the trading book. The document will be for internal use and will go to Group Risk ModelValidation for sign off but also ultimately be available to the PRA. Key Activities The consultant will be involved in writing and collating the information for this document More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
BDO
with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines) Version Control (Git … risk trends over financial years Exploratory Data Analysis (EDA): To spot early signals or risk clusters Desirable: Rank Aggregation/Ensemble Techniques: Understanding methods like Robust Rank Fusion (RRF) Model Explainability Tools: e.g. SHAP, LIME to support interpretability Experience with Model Monitoring & Drift Detection Experience in RegTech/FinCrime/Data-led Supervision Projects is a plus Additional More ❯