51 to 75 of 106 Anomaly Detection Jobs in London

finance. AI-augmented, intelligent finance. You own the design of the AI and machine-learning use cases that make planning better — predictive forecasting, anomaly detection, automated variance analysis, AI-generated commentary and agentic planning workflows among them — and the human-in-the-loop controls that keep finance ...

Google Cloud security best practices and IAM implementation Experience with Google Cloud data services including BigQuery and Dataflow Experience with cloud cost management (budgeting, anomaly detection, cost analysis and reporting) Experience working on a geographically distributed team across time zones Nice to have: Google Cloud Professional certifications ...

where today there is manual effort at every step. Smart and Proactive Controls Moving from reactive error correction to proactive intelligence — embedding AI‐powered anomaly detection, predictive oversight, and intelligent exception management across the full Fund Services operating model. Issues are identified and resolved before they reach ...

emerging risks, influencing product strategy, and serving as the subject matter expert for the SecOps and Vulnerability Management strategy as well as embedding detection and response capabilities on a modern technology stack. You will collaborate globally, supporting audit, regulatory, and risk initiatives, with a focus on cloud computing … resiliency, and auditability expectations. Preferred Qualifications, Capabilities, and Skills: Experience deploying AI-native capabilities within Google SecOps, leveraging Gemini-powered intelligence and ML-based anomaly detection to enhance UEBA and accelerate SOC triage at scale. Experience partnering with Red/Purple Teams to simulate attacks and actively ...

loop controls. Structured extraction: Schema‐driven pipelines over unstructured text (and other modalities) using retrieval, tool‐use, and robust LLM prompting. Hybrid anomaly detection: Blend classical time‐series methods (e.g., decomposition, change‐point, forecasting) with LLM‐aware, contextful detectors for seasonality, spikes, step‐changes, and drift. Novelty … wizardry; GPU/accelerator experience. Multimodal pipelines (text + voice + screenshots). Prior experience in contact center/CX analytics or novelty/anomaly systems. Founder or founding engineer experience #J-18808-Ljbffr ...

governance and design documentation. Develop data quality frameworks, governance policies, schemas and metadata repositories. Integrate AI and machine learning into data solutions, including automation, anomaly detection and predictive data quality. Support data visualisation and translate complex data into actionable insights. Prototype and assess new architecture methods, tools ...

Experience in global data operations or support roles within the financial industry, with a track record of delivering high-quality data solutions. Exposure to anomaly detection methods, statistical tools, and best practices for managing data quality workflows. Excellent communication skills, with experience collaborating across technical, investment ...

with a demonstrable track record delivering the value described for this role* Experience with methods, tools, statistics, and best practices for autonomous and discretionary anomaly detection, and data quality workflow* Excellent written and verbal communication skills; experience working with technical, investment and senior leadership teams* Experience ...

data quality, consistency, and auditability through validation, reconciliation, and documentation of data flows Drive efficiency through automation and AI‐supported data transformation, validation, and anomaly detection Manage and optimise Power BI environments, including datasets, refresh processes, performance tuning, and access control Provide ongoing reporting support, resolving data ...

development efforts Evaluate emerging technologies and recommend strategic improvements to enhance data acquisition capabilities and overall platform performance Develop innovative approaches to data profiling, anomaly detection, and quality metrics reporting that provide stakeholders with comprehensive visibility into data health and lineage Establish and maintain documentation standards, best ...

optimisation initiatives by helping analyse resource utilisation, configuration efficiency, tagging hygiene, and commitment strategies. Advanced Analytics Support: Assist in producing usage trend analysis, anomaly detection, forecasting support, and cost modelling for customer accounts. Reporting & Dashboards: Prepare and maintain financial reports, dashboards, optimisation summaries, and KPI metrics ...

Code (IaC) is the organisational default and challenge inefficient legacy processes. FinOps & Governance: Enforce strict automated security and cost controls, real‐time cost‐anomaly detection, and cost estimation into the Software Development Life Cycle (SDLC) as a standard. Understanding of OpenTelemetry or other telemetry approaches. Internal Platform ...

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 ...

work on include intelligent data extraction from unstructured and semi-structured documents, content classification and routing, cross-language translation, fraud and document-tampering detection, and workflow optimisation across business processes. You'll be trusted to turn ambiguous, often first-of-a-kind problems into dependable services that … regulatory and compliance requirements. Experience building production systems for one or more of: document/data extraction, NLP-based classification, machine translation, fraud or anomaly detection, or workflow automation. Experience evaluating the performance of Generative AI applications – exposure to Mlflow, experiment design, evaluation methodologies. Strong background ...

data transformation-heavy pipelines from data-profiling to cleansing to standardization, conformance and publishing Advanced knowledge of SQL for profiling, joins/merges, deduplication, anomaly detection, and performance tuning Scripting knowledge in Python for automation, parsing, rules engines, and data quality checks, ability to write maintainable code. ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation — helping the team move faster and deliver more scalable, proactive insights. ...

actionable recommendations that improve customer journeys. Advancing AI-native analytics : Leverage Gen AI tools to automate recurring insight generation, support AI-powered summarization and anomaly detection, and identify opportunities to replace manual workflows with intelligent automation - helping the team move faster and deliver more scalable, proactive insights. ...

backend API services, model integration, model monitoring, evaluations and deployments Engineer feature and context pipelines balancing batch and streaming patterns to feed forecasting and anomaly‐detection models, collaborating closely with data scientists to productionise algorithms. Build the data plane for evaluation , implementing rigorous frameworks to continuously monitor ...

/GCP Pub/Sub and post-pass analysis via Athena/BigQuery. Apply AI/ML tools to engineering workflows: LLMs for documentation, anomaly detection on RF telemetry, AI-assisted simulation. Provide third-line RF support to Operations and NOC, including on-call rota participation. Produce ...

/Service/Marketing Cloud, integrations, or Apex best practices). Experience applying AI/ML in engineering workflows (e.g., coding assistants, test generation, anomaly detection, intelligent routing) or product features. Background in leading distributed teams and large‐scale refactoring or platform modernisation initiatives. Key Behaviours & Attributes ...

integrated audits and cross-functional initiatives, connecting IT controls to their financial statement impact. Leverage AI tools and data analytics to scale control testing — anomaly detection, reconciliation validation, workpaper drafting — with appropriate guardrails for SOX and financial data. Train and mentor control owners and internal audit team ...

ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc. Tabular ML: feature engineering, structured data modelling (GBDTs, etc.) Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc. Deep understanding of the GenAI landscape and agentic frameworks. Experience working in the full model lifecycle (including experimentation ...

canary releases, blue/green deployments, feature flags or chaos/game days. Experience developing AI-assisted operations capabilities, such as alert enrichment, anomaly detection, triage support or runbook automation. Reliability engineering: SLOs, SLIs, error budgets, incident reduction and service health. Production excellence: monitoring, alerting, observability, runbooks ...

near-real-time data flows. Shape the architecture for AI-enabled Financial Crime capabilities, including alert optimisation, investigation summarisation, adverse media triage and anomaly detection. Ensure AI and data capabilities are explainable, auditable and appropriate for a highly regulated environment. Establish architecture standards across security, resilience, data lineage, model ...

near-real-time data flows. Shape the architecture for AI-enabled Financial Crime capabilities, including alert optimisation, investigation summarisation, adverse media triage and anomaly detection. Ensure AI and data capabilities are explainable, auditable and appropriate for a highly regulated environment. Establish architecture standards across security, resilience, data lineage, model ...