26 to 50 of 461 Validation Jobs in London

experience working alongside credit analysts and portfolio managers. Exceptional analytical and problem-solving skills with the ability to interpret complex data and investment processes. Proficiency in: SQL - for data validation and exploration. AWS - particularly data services (e.g., S3, Redshift, Lambda). Python - for prototyping analytical tools and performing data analysis. Strong command of business analysis practices, including: Use case and More ❯

making. Write complex SQL queries for data extraction, transformation, and analysis. Support the development and testing of data pipelines, reports, and dashboards. Assist in UAT (User Acceptance Testing) and validation of end-to-end solutions. Prepare BRD, FRD, use cases, process flows, and mapping documents. Collaborate on solution design, data architecture, and systems integration (e.g., with core banking, payment gateways More ❯

with a focus on high-performance multi-station munitions launch systems. What You'll Be Doing: Perform systems engineering tasks including technical planning, integration, risk analysis, and verification/validation across complex aerospace products. Contribute to the full development cycle: concept, design, fabrication, testing, installation, operation, and maintenance. Translate customer and product requirements into robust system solutions, managing trade studies More ❯

an understanding of Software, Electrical and Mechanical Engineering An appreciation of designing complex products Systems design experience Experience of working throughout the development lifecycle (design through to integration, verification, validation, and qualification) Expertise in trade-off analysis Technology insertion (e.g. Urgent Capability Requirements) Supporting to in-service products/systems and quality/issue resolution (e.g. experience of structured problem More ❯

governance, project management and business analyst background. Must demonstrate strong capability to define and articulate approach Technical skills (50%) (Must have) Hands-on experience in defining and leading model validation and system tuning from inception to completion Hands-on understanding on minimum of one TM systems, rule designs, segment designs, technical design and processes (e.g NICE Actimize, Oracle Mantas, SAS More ❯

develop tools for on-demand analysis. Create and manage user-friendly interfaces for data input and operational support. Document systems and processes to ensure transparency and maintainability. Implement data validation and quality monitoring systems. Develop automations to support compliance and record-keeping (e.g., meeting logs, research sources). Stay abreast of emerging technologies and industry trends. Recommend and implement enhancements More ❯

a technical or quantitative field (e.g., Mathematics, Physics, Engineering, or Quantitative Finance); a PhD or equivalent experience is a plus. Experience in a front-office, financial engineering, or model validation role, with expertise in derivatives and structured products, including pricing, valuation, and risk management. Strong quantitative and analytical skills, with a deep understanding of market conventions, derivative structures, and risk More ❯

and domain experts to translate strategic goals and customer needs into practical, scalable ML solutions. Drive model development end-to-end, from exploratory analysis, feature design, and prototyping to validation and deployment. Collaborate with platform and infra teams to operationalize models and ship ML-powered features into production. Continuously assess and iterate on production models, balancing long-term ML strategy More ❯

effective reporting solutions Identifying trends and opportunities in data that support strategic decision-making and business growth Ensuring data accuracy, consistency, and integrity through best practices in data modelling, validation, and governance Working in agile environments to deliver timely, high-quality solutions. What will I be gaining?A solid foundation through a one-week technical and professional skills training programme. More ❯

Build various data visualizations to 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 - 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience - Experience with data 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, or data.table/R. Experience working with AWS or other cloud platforms. Knowledge of building and monitoring high-performance, concurrent services. More ❯

the global/mandate processes are secured. Support Operations in complex and high-impact issues and problems as they arise. Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products. Support product managers on lifecycle management for More ❯

develop accurate, commericalizable financial models. Collaborate closely with engineering, data science, product management, and commercial teams to maintain and enhance model features, data pipelines, and analytical tools. Ensure model validation, back-testing, and continuous performance assessment, prioritizing scalability, reliability, and integrity. Provide thought leadership and strategic guidance on quantitative analytics across the firm and ultimately the broader market. Engage directly More ❯

experience in tracking execution, managing team tasks, and delivering regular progress reports and insightsto leadership and stakeholders. Familiarity with the Model Risk Management (MRM) lifecycle, including model documentation, testing, validation, and alignment with governance and compliance frameworks. Proficiency in Pythonand tools such as LangChain, Pandas, PyTorch/TensorFlow, and FastAPI. Strong understanding of prompt engineering, RAG pipelines, vector databases (e.g. More ❯

AWS and Databricks) Hands-on experience with building data pipelines in Spark within live production environments Coding transformation processes using tools such as dbt Implementing data quality checks and validation Applying CI/CD concepts and using version control systems (e.g., Git) Developing internal front-end applications using Streamlit, Dash, or React (preferred but not essential) Leveraging ML or LLM More ❯

machine learning operations: a) Model Evaluation: Expanding LLM-based audit platform to support multilingual and multimodal auditing. Developing an LLM-powered testing framework for conversational systems to automate the validation of conversational flows, ensuring scalable, accurate, and efficient end-to-end testing. b) Guardrails: Building common guardrail APIs that teams can integrate to detect and prevent egregious errors, knowledge grounding More ❯

ability to multitask in a fast-paced, exciting environment to deliver financial support to client-facing teams. Responsibilities Responsibilities: The ideal candidate is passionate about finance, loves spreadsheets, data validation, and problem solving. Producing monthly P&L reports, investigating variances to forecast and analysing profitability at a project and account level. Understanding key financial drivers such as pricing, staffing mix More ❯

for engineering, test and ongoing service delivery An understanding of Infrastructure as Code concepts (Demonstrable Terraform experience a plus) Demonstrable experience of Data Pipeline testing, including automated testing, data validation and code assurance Demonstrable experience of working within Agile Delivery projects An understanding of data formats for ingest, transformation and analytics, data security, access control and authorisation, GDPR, data privacy More ❯

the global/mandate processes are secured Support Operations in complex and high impact issues and problems as they arise. Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products Support product managers on lifecycle management for More ❯

for the layout of designed blocks and review layout work. Document own work for peer-review and perform design reviews of other team members work. Support the post-silicon validation and characterization of designed RF blocks. Experience - Essentials Experience in heavy research -oriented environments Demonstrated experience of CMOS RF IC design in sub-10GHz frequencies for low power systems. Industry More ❯

the global/mandate processes are secured * Support Operations in complex and high impact issues and problems as they arise. * Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products * Support product managers on lifecycle management for More ❯

the global/mandate processes are secured * Support Operations in complex and high impact issues and problems as they arise. * Accountable for process and technical knowledge gathering, update and validation of products and services under Reporting and Analytics tower, including documentation/knowledge from external teams that will touch those services and products * Support product managers on lifecycle management for More ❯

opportunities and actionable insights Proactively suggest areas for investigation and improvement within the product Design and execute quantitative and qualitative analyses to support product development, roadmap prioritization, and feature validation Develop dashboards and reports to track key product metrics, providing ongoing visibility to stakeholders across the business and promoting data-driven decision making within your teams ad wider business Work More ❯

level of mathematical competence and 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. A leadership mindset focussed on growing the technical capabilities of the More ❯

You have a good understanding 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 for you? You will be More ❯