23 of 23 Permanent Anomaly Detection Jobs in London

Own and evolve the firm’s AI/ML strategy, aligning use cases with product goals and FS client pain points. Lead the development of ML models for classification, anomaly detection, NLP, and predictive analytics using Python, scikit-learn, PyTorch, or similar tools. Collaborate with data engineering to build reliable, secure, and scalable data pipelines that support … Nice to Have: Experience in RegTech, capital markets, or post-trade analytics. Experience working in B2B SaaS. Knowledge of Snowflake, dbt, or related cloud data warehousing technologies. Background in anomaly detection, rule-based AI, NLP, or data reconciliation. Familiarity with regulatory regimes such as EMIR, SFTR, MiFID II, or CFTC. Hands-on experience with version-controlled notebooks More ❯

Own and evolve the firm’s AI/ML strategy, aligning use cases with product goals and FS client pain points. Lead the development of ML models for classification, anomaly detection, NLP, and predictive analytics using Python, scikit-learn, PyTorch, or similar tools. Collaborate with data engineering to build reliable, secure, and scalable data pipelines that support … Nice to Have: Experience in RegTech, capital markets, or post-trade analytics. Experience working in B2B SaaS. Knowledge of Snowflake, dbt, or related cloud data warehousing technologies. Background in anomaly detection, rule-based AI, NLP, or data reconciliation. Familiarity with regulatory regimes such as EMIR, SFTR, MiFID II, or CFTC. Hands-on experience with version-controlled notebooks More ❯

Own and evolve the firm’s AI/ML strategy, aligning use cases with product goals and FS client pain points. Lead the development of ML models for classification, anomaly detection, NLP, and predictive analytics using Python, scikit-learn, PyTorch, or similar tools. Collaborate with data engineering to build reliable, secure, and scalable data pipelines that support … Nice to Have: Experience in RegTech, capital markets, or post-trade analytics. Experience working in B2B SaaS. Knowledge of Snowflake, dbt, or related cloud data warehousing technologies. Background in anomaly detection, rule-based AI, NLP, or data reconciliation. Familiarity with regulatory regimes such as EMIR, SFTR, MiFID II, or CFTC. Hands-on experience with version-controlled notebooks More ❯

Own and evolve the firm’s AI/ML strategy, aligning use cases with product goals and FS client pain points. Lead the development of ML models for classification, anomaly detection, NLP, and predictive analytics using Python, scikit-learn, PyTorch, or similar tools. Collaborate with data engineering to build reliable, secure, and scalable data pipelines that support … Nice to Have: Experience in RegTech, capital markets, or post-trade analytics. Experience working in B2B SaaS. Knowledge of Snowflake, dbt, or related cloud data warehousing technologies. Background in anomaly detection, rule-based AI, NLP, or data reconciliation. Familiarity with regulatory regimes such as EMIR, SFTR, MiFID II, or CFTC. Hands-on experience with version-controlled notebooks More ❯

of rough path theory and modern machine learning. This ambitious, multi-institutional collaboration aims to redefine how streamed data is modelled and processed-unlocking new capabilities in generative AI, anomaly detection, and real-time decision-making. What you would be doing Key scientific challenges you'll help tackle: Next-generation Transformers: Develop mathematically grounded architectures for continuous … multimodal data streams. Efficient Representations: Create robust, interpretable, and scalable representations using signature and path development techniques Anomaly Detection: Build principled, representation-invariant methods for identifying outliers in high-dimensional data with use in appllications. The postholders will be expected to make significant contributions to the mathematical foundations of the programme, engage actively with the broader DataSıg More ❯

of rough path theory and modern machine learning. This ambitious, multi-institutional collaboration aims to redefine how streamed data is modelled and processed-unlocking new capabilities in generative AI, anomaly detection, and real-time decision-making. What you would be doing Key scientific challenges you'll help tackle: Next-generation Transformers: Develop mathematically grounded architectures for continuous … multimodal data streams. Efficient Representations: Create robust, interpretable, and scalable representations using signature and path development techniques Anomaly Detection: Build principled, representation-invariant methods for identifying outliers in high-dimensional data with use in appllications. The postholders will be expected to make significant contributions to the mathematical foundations of the programme, engage actively with the broader DataSıg More ❯

access controls, and auditing). Collaborate with finance and data teams to define data models, schemas, and governance policies that support modern finance workflows, including automated reporting, forecasting, and anomaly detection. Implement data retrieval mechanisms optimized for LLM-based querying via Co-pilot and/or similar tools, enabling natural language access to financial data while maintaining accuracy and More ❯

and billions of transactions annually. Leveraging proven data science, including our proprietary consortium data, our customers use our risk-based, machine learning platform to deliver the highest fraud detection rates, lowest false positive rates, and lowest customer intervention in the industry. We stop fraud, not customers. See what others can't at What you'll achieve As a … analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Qualifications Bachelor's degree in Data Science, Computer Science, or a related field. Doctorate in a … of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is a major advantage. Advanced proficiency in Python for data science and machine learning applications. Familiarity with cloud-based infrastructure, preferably Azure. Expertise with Data Warehousing/ More ❯

completeness, timeliness, and consistency across systems. Utilise Monte Carlo for data observability, proactively detecting and resolving data quality issues. Work with data engineering teams to establish validation, profiling, and anomaly detection frameworks. Stakeholder Engagement & Support Act as a bridge between business and technical teams, ensuring alignment of data requirements. Provide training and guidance to business users on More ❯

aligned with business goals, such as predictive analytics for financial forecasting and automated decision-support systems. You will design, develop, and deploy machine learning models to improve features like anomaly detection, intelligent invoicing, and real-time expense optimization. You will integrate AI into the core platform using frameworks like Laravel or Symfony, ensuring scalability for web and More ❯

aligned with business goals, such as predictive analytics for financial forecasting and automated decision-support systems. You will design, develop, and deploy machine learning models to improve features like anomaly detection, intelligent invoicing, and real-time expense optimization. You will integrate AI into the core platform using frameworks like Laravel or Symfony, ensuring scalability for web and More ❯

aligned with business goals, such as predictive analytics for financial forecasting and automated decision-support systems. You will design, develop, and deploy machine learning models to improve features like anomaly detection, intelligent invoicing, and real-time expense optimization. You will integrate AI into the core platform using frameworks like Laravel or Symfony, ensuring scalability for web and More ❯

aligned with business goals, such as predictive analytics for financial forecasting and automated decision-support systems. You will design, develop, and deploy machine learning models to improve features like anomaly detection, intelligent invoicing, and real-time expense optimization. You will integrate AI into the core platform using frameworks like Laravel or Symfony, ensuring scalability for web and More ❯

aligned with business goals, such as predictive analytics for financial forecasting and automated decision-support systems. You will design, develop, and deploy machine learning models to improve features like anomaly detection, intelligent invoicing, and real-time expense optimization. You will integrate AI into the core platform using frameworks like Laravel or Symfony, ensuring scalability for web and More ❯

and investment planning. Knowledge of KPIs and ability to architect solutions that improve financial and operational performance. Exposure to AI/ML use cases in corporate functions (e.g. finance anomaly detection, HR attrition modelling, procurement spend analytics) Job Offer Competitive salary of £100,000 to £130,000 per annum. Bonus target of 18% to reward performance. Private More ❯

principles and statistical modeling. Day-to-day responsibilities include: Collaborate with other Data Scientists and Machine Learning Engineers to design and implement analytical approaches that inform scalable threat detection models. Partner with threat intelligence analysts to understand emerging attack techniques and leverage data to develop novel detection strategies and expose findings. Perform in-depth data analysis … to identify trends, relationships, and anomalies within vast security datasets. Develop, validate, and refine statistical and machine learning models for threat detection and intelligence generation. Monitor the performance of analytical models and threat intelligence pipelines, continuously identifying opportunities for improvement and refinement. Investigate and resolve data-related issues in production environments, ensuring the accuracy and integrity of our … to support your learning on the job, but prior experience is a plus: Experience with large-scale data processing frameworks (e.g., Spark, Flink). Experience with time series analysis, anomaly detection, or graph analytics in a security context. Proficiency in data visualization tools and techniques to effectively communicate complex findings. A basic understanding of the cyber threat More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

contextualisation, and decision-making using advanced AI models. Intelligent Interfaces: Develop adaptive, conversational UI/UX elements powered by LLMs and logic-driven agents. Analytics & Insights: Build predictive analytics, anomaly detection, and KPI dashboards that empower clients to act with confidence. AI Orchestration (MCP): Oversee integration of Model Context Protocol across product modules for scalable, context-aware More ❯

in applying statistical models for large-scale application and building automated analytical systems Preferred Qualifications Experience in a least one area of Machine Learning (NLP, Regression, Classification, Clustering, or Anomaly Detection) Experience with fairness in machine learning and artificial intelligence to detect and remove bias in ML/AI systems Bachelor's degree in Computer Science or More ❯

Azure AD, or similar identity providers Strong familiarity with Open Policy Agent (OPA) or other policy-as-code tools Exposure to AI/ML for access behavior analytics or anomaly detection Experience implementing Zero Trust architectures, service mesh, or secure infrastructure IAM Comfort working across platform engineering, infrastructure, and product teams About MSCI: What we offer you More ❯

Skills & Expectations: Strong expertise in AI safety tools (e.g., Responsible AI Toolbox, Deepchecks) Experience with LLM compliance testing frameworks Hands-on knowledge in: Prompt injection testing and AI behaviour anomaly detection Bias, fairness, and explain ability metrics for LLMs Audit trail generation, logging, and compliance reporting (GDPR/DSAR) Security risk mitigation in AI agent systems More ❯