51 to 75 of 801 Validation Jobs in London

APIs, databases, financial data providers) into the Azure Databricks platform. Optimise data pipelines for performance, efficiency, and cost-effectiveness. Implement data quality checks and validation rules within data pipelines. Data Transformation & Processing: Implement complex data transformations using Spark (PySpark or Scala) and other relevant technologies. Develop and maintain data processing More ❯

of training data. Design and develop methodologies and metrics to better understand the underlying quality, structure and distribution of training data. Architect training data validation, integrity and safety mechanisms for state-of-the-art ML models. Be given a high degree of autonomy and ownership over your work. Co-hire More ❯

testing Implement explainability frameworks for model transparency and compliance Collaborate with stakeholders to translate business needs into technical solutions Conduct rigorous model testing and validation Prepare documentation and reports communicating complex insights accessibly Stay updated with academic research and industry advancements in optimization and AI/ML Share knowledge and More ❯

of training data. Design and develop methodologies and metrics to better understand the underlying quality, structure and distribution of training data. Architect training data validation, integrity and safety mechanisms for state-of-the-art ML models. Be given a high degree of autonomy and ownership over your work. Co-hire More ❯

tell the story and let the data speak for itself Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation Build automation to reduce dependencies on manual data pulls etc. BASIC QUALIFICATIONS 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL More ❯

compliance with WPP standards. Collaborate with stakeholders to identify business needs and translate these into scalable, impactful technical solutions. Conduct rigorous model testing and validation for robustness and accuracy. Prepare detailed documentation and reports to communicate complex model behaviors, predictions, and insights to both technical and non-technical audiences. Stay More ❯

trading strategies. Collaborate with traders, structurers, and risk managers to deliver robust analytical tools and pricing solutions. Ensure model governance compliance, including documentation and validation support. Contribute to innovation in pricing methodologies, numerical techniques, and model efficiency improvements. Conduct scenario analysis and stress testing for complex structured products. Essential Skills More ❯

join an area that touches every aspect of Amazon's wide range of businesses globally. Key job responsibilities • Independently work on finance requirements analysis, validation, verification and approval, ensuring that requirements are complete, consistent, feasible and traceable. • Translate business and customer requirements, leveraging process and data analysis mechanisms to provide More ❯

proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop More ❯

Leadership and Principal Engineers, focusing on scalable, automated, and maintainable systems. • Champion and embed ML Ops best practices - including model lifecycle management, testing and validation, deployment (CI/CD) and serving, monitoring and observability. • Collaborate with Tech Leadership to drive forward-looking architectural decisions, modernise infrastructure, and reduce technical debt More ❯

clean, and transform healthcare data from various sources such as EHR systems, APIs, and databases. Ensure data quality and integrity through robust testing and validation processes. Optimize storage solutions for structured and unstructured healthcare data using databases (e.g., MongoDB) and cloud-based data warehouses (e.g., Azure Cosmos, Azure Fabric). More ❯

Systems Integration (SI). Product Integration. Design to Cost/Value Engineering (DtC). Configuration and Change Control Management (CM & CC). Verification and Validation (V&V). Specialist Systems Engineering discipline activities (e.g. Safety, Reliability, Availability, Maintainability, EMC, Human Factors, etc.) Delivery of Systems Engineering Deliverables within time and More ❯

of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation and alerting. Location? Hybrid, with 2-3 days working from Daintta office (London or Cheltenham) or on client site as required. What's in it More ❯

of coding best practices and design patterns and experience with code and data versioning, dependency management, code quality and optimisation, error handling, logging, monitoring, validation, and alerting. Location? Hybrid, with 2-3 days working from Daintta office (London or Cheltenham) or on client site as required. What's in it More ❯

self-service analytics and consistent, high-quality metrics by building and maintaining semantic metric definitions and key dashboards. Implement data quality monitoring and data validation throughout the data models you build to ensure high reliability. Collaborate with stakeholders at all levels of the business to understand their data needs and More ❯

to uncover insights, identify trends, and support stakeholders in solving business challenges and making informed decisions. Building and maintaining data pipelines to enable automation, validation, and reporting processes. Collaborating with stakeholders to align data science initiatives with organizational objectives, including designing and executing A/B tests. Developing analytical tools More ❯

to uncover insights, identify trends, and support stakeholders in solving business challenges and making informed decisions. Building and maintaining data pipelines to enable automation, validation, and reporting processes. Collaborating with stakeholders to align data science initiatives with organizational objectives, including designing and executing A/B tests. Developing analytical tools More ❯

Proven experience building back-end application components and APIs in Python Proficiency in designing and executing complex prompt strategies and intput/output data validation models to achieve desired outputs from LLMs Experience monitoring AI applications using popular observability tools (e.g. Langfuse, Langsmith) to ensure seamless performance and monitoring Strong More ❯

MTM valuation, including daily explanations on applicable metrics and limits. Coordinate and review deal and price in trading system by performing deal check, price validation, curve update, and data reconciliation. Monitor timely deal capture, internal trading limits, and risk policy requirements to ensure the representativeness and integrity of transactions in More ❯

ensure seamless integration and adoption of Workday solutions. Providing subject matter expertise and best practices in Workday functionality and processes. Conducting system testing, data validation, and support user acceptance testing (UAT). Mentoring junior consultants and support knowledge sharing across the team. Troubleshooting and resolve complex issues related to Workday More ❯

and Extract, Transform, and Load (ETL) development concepts Understanding of Markit EDM Matcher, Load and Export, EDM UI Experience creating user interfaces and error validation routines in Markit EDM Understanding of batch scheduling system usage and implementation concepts Understanding of MSBI stack - SSIS, SSRS, SSAS A dedication to continuously learn More ❯

required Further develop and maintain in house process for managing and reporting exposure to Natural Catastrophe and Non-Natural Catastrophe events Assist in model validation to help inform view of risk Complete data quality checks as and when required Demonstrate strong problem solving/numerical ability by possessing a minimum More ❯

product and data science management to develop key results for given product objectives. Establish scalable and efficient practices for data mining, ML model development, validation and inference. Stay up-to-date on the most recent advances in AI and machine learning Requirements: PhD Degree in Computer Science, Artificial Intelligence, Mathematics More ❯

Growth: Be part of an international team collaborating with professionals in London, Paris, New York, and Singapore while tackling high-impact projects like model validation, VaR enhancement, and new product onboarding. Diverse Responsibilities: From month-end valuation controls to process improvement and change management, no two days will be the More ❯

Growth: Be part of an international team collaborating with professionals in London, Paris, New York, and Singapore while tackling high-impact projects like model validation, VaR enhancement, and new product onboarding. Diverse Responsibilities: From month-end valuation controls to process improvement and change management, no two days will be the More ❯