1 to 25 of 44 Remote/Hybrid Anomaly Detection Jobs in London

work will help reduce manual effort and enable services to deliver accurate, timely customer migrations Key Responsibilities: Apply classification, regression, ranking, forecasting, clustering, and anomaly detection to enterprise AI and agentic use cases. Develop and evaluate intent classification, semantic matching, agent/skill/tool ranking … embeddings, and LLM-based baselines. Use statistical modeling to estimate execution latency, token demand, inference costs, workload trends, and resource requirements. Apply clustering and anomaly detection to identify recurring intents, capability gaps, unusual agent behavior, and execution regressions. Conduct exploratory analysis, dataset preparation, feature engineering, hypothesis testing ...

from AML, KYC, transaction monitoring, screening, CRM and other operational systems. AI and automation: Build reliable, well-governed datasets that support future machine learning, anomaly detection, alert optimisation and investigation automation. What I’m looking for The most important requirement is someone with genuine technical depth across … financial crime platforms, CRM systems and third-party vendor APIs. Data Vault, dimensional modelling or complex entity resolution. Building data foundations for machine learning, anomaly detection or GenAI applications. Experience with Azure Data Factory, Airflow or similar orchestration technologies. Why consider it? This is an opportunity ...

contracts, capabilities, consumption patterns and priorities for internal and external use cases. Identify opportunities to leverage AI and machine learning to improve data classification, anomaly detection, validation, conflict resolution and other data‐intensive workflows. Work with Data Operations to move towards an exception‐based operating model, where … real‐time or near‐real‐time data processing. Experience applying AI/ML to geospatial or data‐quality problems, such as feature extraction, classification, anomaly detection or automated validation. Experience building developer‐facing products, APIs, SDKs or data services. Experience taking a platform from early‐stage architecture ...

merchant fraud, abuse, chargebacks, and anomalous behaviour. Lead the adoption of modern modelling techniques, including: Transformers and sequence models Representation learning & embeddings Autoencoders and anomaly detection Graph/network-based models Semi-supervised and weakly supervised learning Own the end-to-end model lifecycle: problem framing, feature … Technical Skills: Expert-level Python and modern ML tooling. Strong hands-on experience with: Transformers, LSTM/sequence models Representation learning & embeddings Autoencoders & anomaly detection Experience operationalising models on AWS SageMaker (or equivalent). Strong understanding of model evaluation, explainability, and monitoring in high-risk environments. What ...

Effective collaboration within multidisciplinary teams, supported by strong problem-solving, documentation and critical-thinking skills.**Desirable Skills & Experience*** Advanced statistical modelling, experimental design, forecasting, anomaly detection, model optimisation or explainability.* Deployment and operation of machine-learning models, including monitoring, drift detection and performance management.* Awareness ...

collaboration within multidisciplinary teams, supported by strong problem-s solving, documentation and critical-thinking skills. Desirable Skills & Experience Advanced statistical modelling, experimental design, forecasting, anomaly detection, model optimisation or explainability. Deployment and operation of machine-learning models, including monitoring, drift detection and performance management. Awareness ...

services, banking, wealth management, aviation, telecoms, public sector, or other regulated industries. Experience with enterprise document intelligence, knowledge graph systems, forecasting platforms, threat intelligence, anomaly detection, or AI-assisted decision systems. Background in designing reusable AI reference architectures and platform patterns. Why This Role This ...

data cataloguing, master data management and enterprise data-quality frameworks. Machine learning and advanced analytics: Experience applying analytical or AI techniques to data quality, anomaly detection or operational automation Cost Optimization: Understanding of Fabric capacity management and cost-efficient solution design. WHAT SUCCESS LOOKS LIKE Synapse workloads ...

libraries such as scikit-learn, TensorFlow, or PyTorch. Practical knowledge of algorithms and techniques such as regression, decision trees, random forest, XGBoost, k-means, anomaly detection, and time series forecasting. Working understanding of model evaluation and explainability concepts, e.g. overfitting, bias, cross-validation. Experience developing and implementing ...

platforms and AI workloads using metrics, logs, traces and telemetry. Establish operational insight models that support proactive decision-making and enable advanced capabilities including anomaly detection, event intelligence, noise reduction and predictive operational analytics.• AI Operations & Service Reliability: Apply reliability engineering principles to AI-enabled services, monitoring ...

especially Java. Demonstrable experience collaborating with engineering on services Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL) Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis Experience with statistical analysis and good presentation skills to drive insight … Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, CI/CD Prior experience in the fraud domain and a strong understanding of fraud detection techniques Experience designing and deploying LLM-based solutions in production We’re people without borders — without judgement or prejudice, too. We want to work ...

especially Java. Demonstrable experience collaborating with engineering on services Experience working with large datasets and data processing technologies (e.g., Hadoop, Spark, SQL) Familiarity with anomaly detection, supervised and unsupervised learning methods, and real-time data analysis Experience with statistical analysis and good presentation skills to drive insight … Airflow, MLflow, AWS SageMaker, AWS S3, AWS EMR, CI/CD Prior experience in the fraud domain and a strong understanding of fraud detection techniques Experience designing and deploying LLM-based solutions in production We’re people without borders — without judgement or prejudice, too. We want to work ...

churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning. Optimization: Building engines for marketing spend, inventory management, or resource allocation. Causal ...

churn, propensity-to-buy, lead scoring, or lifetime value (LTV) to directly drive targeted marketing and product interventions. Applied Forecasting: Time-series forecasting, anomaly detection, or handling non-stationary data for demand or revenue planning. Optimization: Building engines for marketing spend, inventory management, or resource allocation. Causal ...

incident, backup, resilience and monitoring controls. Practical experience applying AI, Agentic AI, AIOps or intelligent automation to operational use cases such as incident triage, anomaly detection, runbook automation, knowledge search, root cause support or service desk workflows. Knowledge of observability and reliability practices, including SRE principles, service ...

software development lifecycle (e.g., automated code reviews, synthesis, workflow orchestration, agent-driven monitoring/troubleshooting). Prototype and evaluate agentic workflows for automated anomaly detection, market data quality validation, and intelligent developer tooling. Technical Leadership & Excellence Drive engineering best practices: test-driven development (TDD), CI/ ...

applied within service management to improve operational efficiency, employee experience and service outcomes.* Awareness of modern AIOps and observability capabilities, including monitoring, event correlation, anomaly detection, intelligent alerting, operational analytics and automation.* Familiarity with enterprise service management platforms such as ServiceNow, Jira Service Management, Freshworks or similar ...

tasks. AIOps & Intelligent Observability: Ability to integrate traditional observability stacks (e.g., Datadog, Prometheus, OpenTelemetry) with AI/ML models to automate root-cause analysis, anomaly detection, and semantic log clustering. Self-Healing Infrastructure Engineering: Experience designing closed-loop, self-healing systems that autonomously execute recovery actions (e.g. ...

huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements ...

huge impact to the security of the UK. Core Duties Design and develop machine learning models for traditional ML use cases (forecasting, classification, anomaly detection) and GenAI/LLM applications Lead experimentation cycles: define hypotheses, design experiments, evaluate results, and iterate rapidly while adhering to governance requirements ...

comparisons and reconciliation checks to validate that migrated data is complete, consistent and faithful. Write reusable SQL and Python scripts for profiling, exception detection and validation, using Azure Databricks, Git and dbt where relevant. Communicate findings clearly to technical and non-technical audiences, using Excel and Power … profiling unfamiliar datasets and tracing data quality issues to their root cause in a migration context. Strong SQL skills for complex joins, window functions, anomaly detection and source-to-target reconciliation. Working knowledge of Python, Azure Databricks or Spark SQL, and familiarity with Git and dbt. Ability ...

weigh evidence across application, document, bank, bureau, dealer and vehicle data, flag suspicious cases and explain why. Develop the models underneath - Build fraud classifiers, anomaly detection, document intelligence and network analysis to uncover linked applications, synthetic identities and dealer collusion. Ship it to production - Own deployment ...

Automation: Select, implement and manage FinOps tooling (native cloud cost management tools, third‐party platforms, BI and reporting tools). Drive automation of reporting, anomaly detection, budget alerts and policy enforcement. Governance, Risk and Compliance: Ensure that financial controls, audit requirements and internal policies are met. Collaborate ...

dataset or collection from nothing, including the unglamorous parts: schema decisions, quality checks, and maintenance. Blockchain or on chain data experience: clustering, attribution, heuristics, anomaly detection, mempool analysis, or research into privacy preserving systems. Experience in payments, fraud or risk data science, where the cost ...

that strengthen our data foundations - ensuring our data is accurate, observable, and compliant. Your mission will be to reduce the mean time to detection and resolution of data incidents, by establishing data contracts between producers and consumers, developing robust data observability systems, and embedding governance and GDPR compliance … bridge technical depth with operational impact. Bonus Points Experience implementing automated compliance monitoring or policy-as-code systems. Familiarity with real-time anomaly detection for data pipelines. Experience contributing to or leading cross-functional data reliability initiatives. Prior experience in consumer or marketplace platforms. Passion for data ...