1 to 25 of 87 Validation Jobs in the City of London

What You’ll Be Doing: Designing and building machine learning models to solve real-world problems Carrying out full data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and AI techniques to generate actionable insights Contributing to experimental research, model prototyping, and A/B testing Presenting findings clearly to both technical and non More ❯

ll Be Doing: Designing and deploying predictive models, machine learning solutions, and advanced statistical analyses Executing end-to-end data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and ML techniques to identify insights from millions of behavioural data points Working closely with product and business teams to translate findings into actionable outcomes Measuring More ❯

ll Be Doing: Designing and deploying predictive models, machine learning solutions, and advanced statistical analyses Executing end-to-end data science workflows: from data acquisition and cleaning to modelling, validation, and deployment Applying statistical and ML techniques to identify insights from millions of behavioural data points Working closely with product and business teams to translate findings into actionable outcomes Measuring More ❯

About the Company A regulated financial markets firm bringing institutional standards to the rapidly evolving digital assets sector. Key Responsibilities Lead Quantitative Model Development: Oversee the creation, validation, and optimization of models for pricing Bitcoin index futures and options, ensuring accuracy, scalability, and regulatory compliance. Risk Management: Develop and refine risk models (e.g., VaR, Expected Shortfall, SPAN) to support trading More ❯

About the Company A regulated financial markets firm bringing institutional standards to the rapidly evolving digital assets sector. Key Responsibilities Lead Quantitative Model Development: Oversee the creation, validation, and optimization of models for pricing Bitcoin index futures and options, ensuring accuracy, scalability, and regulatory compliance. Risk Management: Develop and refine risk models (e.g., VaR, Expected Shortfall, SPAN) to support trading More ❯

those who are keen to immerse themselves in a dynamic and forward-thinking environment. You will have ample opportunity to be involved in exciting project-based work including model validation, event response, and streamlining and automating processes, similarly, you will have the chance to oversee the training and guidance of junior colleagues, making this a great opportunity to step into More ❯

those who are keen to immerse themselves in a dynamic and forward-thinking environment. You will have ample opportunity to be involved in exciting project-based work including model validation, event response, and streamlining and automating processes, similarly, you will have the chance to oversee the training and guidance of junior colleagues, making this a great opportunity to step into More ❯

development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience Analyse credit performance data to generate More ❯

and engineering skills applying a rich universe of external data and emerging risk modelling practices to the understanding, modelling and optimisation of risk exposures. Principal Accountabilities: Lead the preparation, validation, and submission of regulatory reports related to exposure management, ensuring accuracy, completeness, and compliance with regulatory requirements (e.g., RDL/LCM). Analyse large datasets to extract insights related to More ❯

and engineering skills applying a rich universe of external data and emerging risk modelling practices to the understanding, modelling and optimisation of risk exposures. Principal Accountabilities: Lead the preparation, validation, and submission of regulatory reports related to exposure management, ensuring accuracy, completeness, and compliance with regulatory requirements (e.g., RDL/LCM). Analyse large datasets to extract insights related to More ❯

and forecasting libraries. Work with 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. Building demand forecasting models Stay up-to-date on the most recent advances in AI and machine learning Requirements: MSc Degree in Computer Science, Mathematics, Statistics or related More ❯

and deploy custom Salesforce solutions, including Apex, Visualforce, Lightning Components, and integrations with other systems. Customise Salesforce to meet specific business needs by creating custom objects, fields, workflows, and validation rules. Integrate Salesforce with other systems using APIs and middleware tools, ensuring seamless data flow and interoperability. Conduct code reviews and ensure the quality, performance, and security of developed solutions. More ❯

teams responsible for building a user review sentiment analysis tool. Project manage the platform localisation into key languages. Monitor and improve VGI platform data accuracy , including managing ground-truth validation and discrepancy reporting workflows. Set up and maintain tools to analyse usage behavior and inform roadmap decisions. Gather requirements by interviewing customers, internal stakeholders, and reviewing usage data to understand More ❯

life science methodologies, particularly in the areas of drug discovery and assay development. Experience with Design of Experiments (DOE) methodology and understanding of DOE campaign phases (Screening, Optimization, Robustness & Validation). Ability to analyze and interpret DOE data using statistical tools such as JMP or the Synthace platform. Possessing strong communication skills, you will act as the expert in the More ❯

life science methodologies, particularly in the areas of drug discovery and assay development. Experience with Design of Experiments (DOE) methodology and understanding of DOE campaign phases (Screening, Optimization, Robustness & Validation). Ability to analyze and interpret DOE data using statistical tools such as JMP or the Synthace platform. Possessing strong communication skills, you will act as the expert in the More ❯

day to day: Develop and maintain IFRS9 and scorecard model Produce model methodology and documentation Interact closely with stakeholders regarding model developments Work closely with data science and model validation teams SKILLS AND EXPERIENCE Experience using Python or R (SAS will be considered) Experience building IFRS9, scorecard or affordability models A strong university degree in a numerate discipline SALARY AND More ❯

day to day: Develop and maintain IFRS9 and scorecard model Produce model methodology and documentation Interact closely with stakeholders regarding model developments Work closely with data science and model validation teams SKILLS AND EXPERIENCE Experience using Python or R (SAS will be considered) Experience building IFRS9, scorecard or affordability models A strong university degree in a numerate discipline SALARY AND More ❯

support experimentation and model development Develop and deploy machine learning models in production environments Present insights and results to technical and non-technical stakeholders Apply statistical methods and model validation techniques to reach accurate conclusions Work with data engineers to ensure clean, usable datasets Contribute to ethical, privacy-aware, and user-centric data products Stay curious, research new methods, and More ❯

This role is ideal for someone experienced in natural catastrophe modelling and confident working with large geospatial and financial loss datasets. You’ll contribute to the development, calibration, and validation of loss models that project climate-related physical impacts such as floods, subsidence, storms, droughts, and wildfires — helping clients assess and manage climate risks effectively. Key Responsibilities Develop loss models More ❯

for full visibility. Attend and actively contribute to workshops and requirements-gathering sessions. Document business processes using BPMN and other modelling tools. Assist senior team members with requirements gathering, validation, and documentation for both BAU and operational readiness change. Contribute to business analysis practice initiatives, including supporting and mentoring junior analysts. What You Will Bring Proven ability to apply business More ❯

for full visibility. Attend and actively contribute to workshops and requirements-gathering sessions. Document business processes using BPMN and other modelling tools. Assist senior team members with requirements gathering, validation, and documentation for both BAU and operational readiness change. Contribute to business analysis practice initiatives, including supporting and mentoring junior analysts. What You Will Bring Proven ability to apply business More ❯

pay accuracy, compliance, and colleague trust during this exciting transformation. What You'll Be Doing: You'll take ownership of the payroll data migration workstream - leading the extraction, transformation, validation and upload of all payroll-related data into HCM. Working closely with HR, Finance, and the HR Data Migration Specialist, you'll ensure payroll and HR datasets are aligned, clean More ❯

genetics or a related field with a strong methodological focus A track record of developing statistical models for genomic/biological research, preferably within a target identification or target validation setting Proven track record of innovation in statistical methodology, evidenced by publications, tools or project delivery Advanced coding skills in a language such as R or python and experience with More ❯

LLMs into RAG pipelines, document intelligence, and agentic workflows Use of vector databases (e.g., FAISS, Pinecone, Chroma) for semantic search and retrieval Implementation of grounding, context injection, and response validation mechanisms Model Context Protocol (MCP) Implement secure, policy-aligned Model Context Protocol (MCP) for managing contextual memory, grounding, and session control in LLM-based systems Enforce context boundary policies, context More ❯

engineering receives well-scoped specifications. Data Operations & Ground Truth – Manage offshore data-labelling teams, creating and refining annotation guidelines while ensuring quality and throughput targets are met. Oversee creation, validation, and improvement of ground-truth datasets that power our AI models. Audit labelled data to identify and correct errors or inconsistencies. AI Evaluation and Improvement – Define accuracy benchmarks and acceptance More ❯