1 to 25 of 57 Anomaly Detection Jobs in London

effectively with stakeholders across data, governance, and infrastructure. Experience in defining quality strategies , driving process improvements, and implementing automation in large-scale data platforms. Knowledge of data observability and anomaly detection tools (preferred). Industry experience in financial services, insurance, or regulated environments (not essential, but preferred). This role is an excellent opportunity for a Lead More ❯

maintain, performance tune, and respond to incidents on our big data pipeline infrastructure. Build out observability and intelligent monitoring of data pipelines and infrastructure to achieve early and automated anomaly detection and alerting. Present your research and insights to all levels of the company, clearly and concisely. Build solutions to continually improve our software release and change More ❯

and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and security measures in line with best practices and regulatory standards. Develop observability and anomaly detection tools to support Tier 1 systems. Work with engineers and business teams to gather requirements and translate them into technical solutions. Maintain documentation, follow coding standards … technical and non-technical teams. Additional Strengths Experience with orchestration tools like Apache Airflow. Knowledge of real-time data processing and event-driven architectures. Familiarity with observability tools and anomaly detection for production systems. Exposure to data visualization platforms such as Tableau or Looker. Relevant cloud or data engineering certifications. What we offer: A collaborative and transparent … Apache Airflow (or similar) and integrating them into containerised CI/CD pipelines (Docker, GitHub Actions, Jenkins, etc.)? Select Which option best describes your experience building observability and automated anomaly detection tooling for data pipelines? Select What best describes your current location and working rights status? Select By submitting your application, you confirm that you have read More ❯

models using relevant datasets to achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining & Analysis Apply data mining techniques such as clustering, classification, regression, and anomaly detection to discover patterns and trends in large datasets. Analyze and preprocess large datasets to extract meaningful insights and features for model training Code Review and Documentation More ❯

models using relevant datasets to achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining & Analysis Apply data mining techniques such as clustering, classification, regression, and anomaly detection to discover patterns and trends in large datasets. Analyze and preprocess large datasets to extract meaningful insights and features for model training Code Review and Documentation More ❯

Route Optimization: Use data analytics to identify the most efficient routes. Optimized routing not only shortens travel time but also makes ETA predictions more reliable. 5. Machine Learning for Anomaly Detection: Implement machine learning algorithms to detect anomalies that could affect delivery times, such as unexpected traffic jams or vehicle breakdowns, and adjust ETAs accordingly. 6. Sensor More ❯

Route Optimization: Use data analytics to identify the most efficient routes. Optimized routing not only shortens travel time but also makes ETA predictions more reliable. 5. Machine Learning for Anomaly Detection: Implement machine learning algorithms to detect anomalies that could affect delivery times, such as unexpected traffic jams or vehicle breakdowns, and adjust ETAs accordingly. 6. Sensor More ❯

s Pricing & Promotions Science, Data, and Insights organization is seeking a highly analytical Business Intelligence Engineer. In this role, you will develop, build, and deliver automated analytics, insights, and anomaly detection tools and technologies, which will deliver the best prices and experiences to our customers. Data, insights, and analytics are at the core of Amazon's culture … Promotions Science organization leverages planet scale multi-modal data on billions of Amazons and external competitor products to build advanced machine learning models for product similarity, substitutability, error detection & correction, and probabilistic price estimation, discovery and discount optimization, promotion & deal recommendation and ranking, and causal short- & long-term impact measurement. We preserve long term customer trust by ensuring More ❯

technical and non-technical teams. Bonus Points For: Experience with orchestration tools like Apache Airflow. Familiarity with real-time data processing and event-driven systems. Knowledge of observability and anomaly detection in production environments. Exposure to visualization tools like Tableau or Looker. Relevant cloud or data engineering certifications. What’s Offered: Competitive salary with two annual discretionary More ❯

technical and non-technical teams. Bonus Points For: Experience with orchestration tools like Apache Airflow. Familiarity with real-time data processing and event-driven systems. Knowledge of observability and anomaly detection in production environments. Exposure to visualization tools like Tableau or Looker. Relevant cloud or data engineering certifications. What’s Offered: Competitive salary with two annual discretionary More ❯

for problem-solving. Preferred Skills: Interest and familiarity with generative AI frameworks. Knowledge of data governance and management, supported by industry certifications (e.g., DAMA CDMP, DCAM). Experience with anomaly detection methodologies. Experience with Agile/Scrum project management methodologies. If this sounds like you, apply to join our team. We will contact you with the next More ❯

for problem-solving. Preferred Skills: Interest and familiarity with generative AI frameworks. Knowledge of data governance and management, supported by industry certifications (e.g., DAMA CDMP, DCAM). Experience with anomaly detection methodologies. Experience with Agile/Scrum project management methodologies. If this sounds like you, apply to join our team. We will contact you with the next More ❯

annotations. Experience in using Bloomberg Data, Bloomberg Terminal, and/or enterprise financial data products. Interest in solving problems and developing data-driven methodologies for high precision & high recall anomaly detection. Past project experience using the Agile/Scrum project management methodology. Does this sound like you? Apply if you think we're a good match. We'll get More ❯

the integrity and security of our payment systems. Your role will involve leveraging data analytical skills, Python, SQL, and various analytical tools to identify suspicious activities, enhance fraud detection strategies, and support decision-making processes. Your New Day-to-day Will Involve Fraud Detection and Analysis: Analyse transaction data to identify patterns and trends indicative of … fraudulent activities. Investigate and monitor real-time transaction alerts to detect potential card fraud. Develop and implement data-driven fraud detection rules and models. Analyse false positives to refine and optimize fraud detection systems. Ensure that the company's financial practices comply with statutory regulations and legislation. Data Management and Analysis: Extract, clean, and manage large … practices for fraud detection. Analytical Mindset: Strong problem-solving skills with a keen eye for detail. Ability to interpret complex data and turn it into actionable insights. Familiarity with anomaly detection and pattern recognition techniques. Communication and Stakeholder Management: Excellent communication skills with the ability to translate complex data findings into clear insights for non-technical stakeholders. More ❯

and optimize data pipelines to ensure performance and cost efficiency. Implement data governance, access controls, and security measures in line with best practices and regulatory standards. Develop observability and anomaly detection tools to support Tier 1 systems. Collaboration & Continuous Improvement Work with engineers and business teams to gather requirements and translate them into technical solutions. Maintain documentation … technical and non-technical teams. Additional Strengths Experience with orchestration tools like Apache Airflow. Knowledge of real-time data processing and event-driven architectures. Familiarity with observability tools and anomaly detection for production systems. Exposure to data visualization platforms such as Tableau or Looker. Relevant cloud or data engineering certifications. What we offer: A collaborative and transparent More ❯

or equivalent industry experience. Preferred Qualifications Experience or interest in mentoring junior engineers. Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow). Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, or data.table/R. Experience working with AWS or other cloud platforms. Knowledge of building and monitoring high-performance More ❯

field, or equivalent industry experience Preferred Qualifications Experience or interest in mentoring junior engineers Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow) Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, data.table/R Experience working with AWS or other cloud platforms Knowledge of building and monitoring high-performance, concurrent More ❯

MySQL Ingestion pipeline for reduced latency and 10x scalability. Redshift -> Snowflake migration Unified Local Analytics Development Environment for Airflow and DBT Building our next generation company metrics framework, adding anomaly detection and alerting, and enabling easier discovery and consumption. About you You have 5+ years of full-time, professional work experience in the data space using Python More ❯

of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail More ❯

of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail More ❯

of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail More ❯

of data models. Communicate complex data insights to non-technical stakeholders through clear and actionable reports. Apply domain knowledge (if applicable) in financial fraud to enhance predictive modelling and anomaly detection capabilities. Skills and attributes for success Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail More ❯

Senior Forward Deployed Data Scientist to implement our ML SaaS platform with major automotive and EV manufacturers. You’ll develop custom Python-based ML solutions for use cases like anomaly detection and time series analysis, bridging implementation gaps. Collaborating with Customer Success, you’ll tackle challenges in ML generalization, guide clients on model performance, and influence product … environments Track record of delivering end-to-end ML projects in production environments It would be a real bonus, but not a requirement if: Experience with time series analysis, anomaly detection, or deep learning Apache Spark knowledge/experience PhD in relevant field, research publications, or contributions to open-source projects Prior experience in successful startups Interview More ❯

a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases). Experience with recent trends such as foundation models , causal inference More ❯

a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying probabilistic models in real-world applications (e.g., recommendation systems, anomaly detection, personalized healthcare, etc.). Understanding of modern ML pipelines and MLOps (e.g., MLFlow, Weights & Biases). Experience with recent trends such as foundation models , causal inference More ❯