6 of 6 DemandTrendPermanent Anomaly Detection Jobs in Central London

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

monitoring and reporting. Technology & Automation · Use Python, SQL, and Databricks to analyse in house data. · Explore opportunities to apply AL and ML models to improve forecasting, scenario tests, and anomaly detection. Requirements · Proven experience in Python, SQL, and Databricks · Experience in building dashboards (Databricks, PowerBI, Tableau, or similar) · Experience in the financial industry · Strong analytical and problem-solving skills More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

and AI-native querying (e.g., Text-to-SQL). Productize the PLuG SDK as a Data Platform: Leverage in-app instrumentation (session replays, logs, engagement events) to power observability, anomaly detection, and customer experience analytics. Build AI-Enabled Interactions: Drive the development of agentic features including natural language queries, AI-generated dashboards, and real-time recommendations—bridging More ❯

models that power live decision-making. What You'll Be Doing: Designing and deploying production-grade ML models that drive live decision-making. Applying computer vision Building fraud and anomaly detection models using geospatial and behavioural signals. Partnering with engineers to scale pipelines, compliance monitors, and detection systems. Leading scientific direction and mentoring other data More ❯

business needs into data-driven solutions Essential skills: Python (pandas, NumPy, scikit-learn) – data wrangling, modelling, feature engineering SQL – querying structured datasets Model Development & Validation – classification, unsupervised learning (outlier detection), ranking models ML Deployment – containerised deployments (Podman, SageMaker, DSW pipelines) Git – version control for reproducible workflows Time-Series Analysis – spotting risk trends over time EDA – identifying early risk … signals and clusters Desirable skills: Rank aggregation/ensemble methods (e.g. Robust Rank Fusion) Model explainability tools (SHAP, LIME) Model monitoring & drift detection Experience in RegTech, FinCrime, or data-led supervision projects Please submit your CV, highlighting relevant experience. More ❯