11 of 11 Remote Anomaly Detection Jobs in London

and network expansion. Partner with commercial and product stakeholders to embed data into every stage of the sales, account management, and network growth processes. Build models for customer segmentation, anomaly detection, forecasting, fraud/risk scoring, and identifying growth opportunities in existing and untapped markets. Turn data into actionable insights, proactively and persuasively translating data into meaning … drive decisions. Nice-to-Haves Experience with forecasting models for revenue, client growth, and network activity. Familiarity with data visualization tools like Tableau. Exposure to fraud detection, anomaly detection and pattern recognition modeling. Create a Job Alert Interested in building your career at Freemarket? Get future opportunities sent straight to your email. Apply for this More ❯

runtime-isolated, reproducible models that are easy to deploy, monitor, and update without connectivity. Work closely with data scientists to define clear KPIs and success criteria-such as detection accuracy, latency, false positive/negative rates, explainability, and robustness-to determine what constitutes a production-grade, releasable model. Align model performance goals with the operational realities of the … and stakeholder management skills. Comfortable working in a fast-paced, iterative, and agile environment. Preferred Experience: Solid understanding of cyber security concepts such as threat detection, SIEM, anomaly detection, and incident response. Experience with tools for tracking ML models in production (e.g., MLflow). We encourage you to apply even if your experience is not More ❯

relationships between metrics and benchmarks. Develop robust Trend Identification models to analyse key metrics, understand evolving trends, and provide actionable insights (e.g., input to pricing, axes). Implement Outlier Detection algorithms to pinpoint unusual data points, enabling investigation of potential risks or opportunities, and build Scenario Planning tools to model the incremental impact of client activities and market … learning, preferably within the financial services industry and ideally within Equities Prime Finance. Demonstrated experience applying AI/ML techniques to complex business problems, focusing on time series analysis, anomaly detection, forecasting, or Natural Language Processing (NLP). Strong proficiency in Python/R and expertise with AI/ML libraries/frameworks (e.g., scikit-learn, TensorFlow More ❯

analysis, or EA, with 5+ years in finance systems. Proven expertise with finance operating models and KPIs (EBITDA, NPV, DSO). Experience with AI/ML in finance (e.g., anomaly detection, predictive AR). Skills & Tools Deep knowledge of SaaS, PaaS, microservices, data analytics, and EA frameworks. Familiarity with IT governance, DevOps, agile methodologies, and financial modeling. 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 ❯

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 ❯

and efficiency. Leverage AWS technologies (S3, Athena, QuickSight) to analyse data from millions of field devices, delivering insights to inform decision-making and drive operational efficiency. Develop and implement anomaly detection techniques and data-driven solutions to proactively identify and resolve system issues. Perform global metric comparisons across various device models. What You'll Bring: You will 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 ❯

objective of the role is to lead a global team that coordinate exceptional Services response to major technology events (planned or unplanned), team responsibilities encompasses oversight of 24x7 service anomaly detection for over 90 critical end to end flows ensuring adherence to regulatory mandated Critical Business Services (CBS) and a heightened focus on a subset of Platinum More ❯