1 to 25 of 61 Remote/Hybrid Anomaly Detection Jobs in the UK

with many different collection techniques, along with internal QA tools. This role will specialise in taking our QA systems further: hardening the validation and anomaly detection that catches problems before our customers do, keeping our scrapers healthy and resilient as sources change under us, and shipping fast … puzzle and wants to own and raise an existing quality bar rather than maintain someone else's. Design and build data quality checks - validation, anomaly detection, freshness and coverage monitoring - across our core data pipelines Own and improve production web scraping infrastructure (Playwright, proxy management, anti ...

domains.* Develop KPI engineering models for network performance, service quality, fault behaviour, customer impact, capacity, and resilience.* Build statistical and machine learning models for anomaly detection, fault prediction, root-cause analysis, degradation detection, and proactive assurance.* Develop data aggregation, cleansing, enrichment, and feature engineering pipelines … topology, or service assurance data.* Understanding of telecom network domains including RAN, Core, IP/MPLS, SD-WAN, Transport, Cloud, or OSS.* Experience developing anomaly detection, fault analysis, predictive analytics, or KPI models.* Experience with data aggregation, cleansing, enrichment, and data quality assessment.* Experience with graph analytics ...

Collaborate with engineering and business stakeholders to identify performance trends, operational opportunities, and actionable insights. Create data pipelines and workflows that support operational monitoring, anomaly detection, service analytics, and business intelligence initiatives. Integrate data from multiple enterprise systems including Azure, SQL databases, APIs, cloud platforms, and operational … Azure Data Factory, Synapse Analytics, Data Lake, or related cloud data technologies. Experience creating executive dashboards and operational reporting solutions. Knowledge of machine learning, anomaly detection, predictive analytics, or statistical analysis techniques. Experience working with large-scale telemetry, operational, or IoT datasets. Familiarity with DevOps practices ...

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 ...

unstructured commercial and operational shipping data such as customs filings, fixtures, and SPAs. These inputs drive predictive systems that support energy-demand forecasting, anomaly detection, and real-time recommendations for physical and derivative trading. What You'll Be Doing As a Principal Data Scientist, reporting toVortexa … depth ofexpertiserather than the credential. Fluent in Python and broad in your modelling toolkit: withstrongexperience across regression and classification, clustering, time-series analysis, anomaly detection, sequence-to-sequencearchitecturesand stochasticoptimisation. Comfortable withsolvingambiguous problems:able to start with an abstract question, interrogate it, decide what is worth solving, choose ...

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 ...

such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. … such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. ...

such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. … such as detection and classification for time series and image/video data streams. Develop and evaluate ML models for behaviour classification, anomaly detection, and track pattern recognition within geospatial data. Research, prototype, extend, and optimise suitable vision and time-series models for these problems. ...

building practical tools to identify and resolve issues before they reach customers. The Role You will: Design and develop data quality checks covering validation, anomaly detection, freshness and coverage. Own and improve production web-scraping infrastructure, including Playwright, proxies and anti-bot handling. Build and maintain data … ship solutions efficiently. About You Strong Python and SQL skills, with hands-on dbt and BigQuery experience. Proven experience designing data quality, validation and anomaly detection processes. Production experience with web scraping at scale, ideally using Playwright or an equivalent. Experience with big data sets ...

translating findings into practical actions. Using your expertise, you'll design and deploy AI-driven security capabilities such as threat detection, anomaly detection and incident response. You'll also advise on risk, compliance and regulation, ensuring we continue to meet industry standards as AI technologies ...

meet evolving analytical and business requirements. Drive high standards of data quality, integrity and governance through the implementation of automated validation, cleansing, monitoring and anomaly detection processes. Integrate, transform and harmonise data from a wide range of internal and external sources, including policy, claims, telematics and third ...

ambitious collaboration between the public, charity and private sectors, designed to help people live healthier lives for longer through better prevention, earlier detection and improved treatment of diseases. We will speed up the discovery of new methods of early disease detection, and the evaluation … ideally genomic data. Developing models, algorithms or rule‐based systems that support human decision‐making, ideally where explainability, auditability and risk management are important. Anomaly detection, behavioural analytics, security monitoring or detection engineering. Risk quantification methods from fields such as actuarial science, epidemiology, operational research ...

platform is adaptable to evolving global compliance standards. AI & Automation Integration:Apply knowledge of AI/ML concepts to explore and implement intelligent automation, anomaly detection, or data classification solutions within the regulatory reporting pipelines. Hands-On Development: Write clean, robust, and testable code using Java ...

deploying machine learning models for risk scoring, compliance prediction, churn analysis and contractor performance analytics Building and deploying LLM-based solutions for text analytics, anomaly detection and automated compliance checks Working with Engineering and Product teams to integrate models into production environments across AWS and Azure Using ...

maintain automation scripts, deployment tooling, and operational workflows. Implement and support observability solutions, monitoring platforms, logging frameworks, and telemetry capabilities. Develop AIOps capabilities for anomaly detection, event correlation, alert noise reduction, and proactive issue identification. Create automated remediation processes, runbooks, and self-healing mechanisms to improve operational ...

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 ...

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 ...

Automated fault detection, Root cause analysis, Dynamic RF optimisation, Automated channel selection, Automated power adjustments, Client steering, Service assurance automation, Network anomaly detection Experience leveraging machine learning and analytics to improve user experience, wireless performance, service availability and operational resilience. Ability to define architectures that ...

other motorsports series. Our software combines many capabilities, including data capture, visualisation and modelling of real time and historic data for detailed analysis, reporting, anomaly detection and enabling the best strategic decisions to be made. Through clean and consistent coding, you will contribute to optimise our methods ...

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 ...

across data initiatives. Develop data quality, governance, metadata and data management frameworks. Explore how AI and Machine Learning can enhance data solutions through automation, anomaly detection and predictive data quality. Translate complex technical concepts and data insights into clear recommendations for senior stakeholders. Contribute to the development ...

scale data platforms. Experience in Broadband, Video, Set-Top Box, embedded devices, networking, RDK, Wi-Fi, or DOCSIS environments. Experience building telemetry-driven diagnostics, anomaly detection, root-cause analysis, observability, or intelligent troubleshooting solutions. Experience optimizing AI/LLM applications for accuracy, reliability, latency, scalability, and cost. ...

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 ...

consumers Design feature stores and data pipelines that support AI/ML model training and inference for use cases such as FX pricing, payment anomaly detection, and limit utilisation forecasting Evaluate and integrate AI‐assisted data tooling (AI‐powered cataloguing, natural language querying, automated data quality) where ...

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 ...