26 to 50 of 76 Model Validation Jobs in London

in the team due to continued success. THE ROLE Lead the end-to-end development of IRB models across a range of clients Assist the wider team with broader model projects including application and behavioural scorecards Work closely with the model validation team to enhance model performance Manage a small team of analysts to drive the More ❯

in the team due to continued success. THE ROLE Lead the end-to-end development of IRB models across a range of clients Assist the wider team with broader model projects including application and behavioural scorecards Work closely with the model validation team to enhance model performance Manage a small team of analysts to drive the More ❯

train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep … train, and deploy state-of-the-art models (e.g., deep learning, NLP, computer vision, reinforcement learning, or relevant domain-specific architectures). Design infrastructure for data ingestion, annotation, experimentation, model versioning, and monitoring. Collaborate closely with product, design, and DevOps to integrate AI features into our platform. Continuously evaluate new research, open-source tools, and emerging frameworks to keep … ML team as we scale beyond our seed round. Key Responsibilities Architecture & Hands-On Development Define and implement end-to-end AI pipelines: data collection/cleaning, feature engineering, model training, validation, and inference. Rapidly prototype novel models (e.g., neural networks, probabilistic models) using PyTorch, TensorFlow, JAX, or equivalent. Productionize models in cloud/on-prem environments (AWS More ❯

drive business outcomes. Key responsibilities include: Designing and building data processing and streaming systems Leading initiatives on data storage, optimisation, and database management Applying statistical methods, hypothesis testing, and model validation Developing and evaluating AI/ML models to deliver actionable insights Collaborating with engineering teams to maintain data quality and scalability Communicating technical concepts effectively to non More ❯

drive business outcomes. Key responsibilities include: Designing and building data processing and streaming systems Leading initiatives on data storage, optimisation, and database management Applying statistical methods, hypothesis testing, and model validation Developing and evaluating AI/ML models to deliver actionable insights Collaborating with engineering teams to maintain data quality and scalability Communicating technical concepts effectively to non 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 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 More ❯

Leader Heads of Departments Tech Leadership Payment and Collections Teams Customer Operations Teams Compliance, Risk & Regs Teams Product & Operations Teams What you'll be getting up to: Data Collection & Validation • Extract payment and collections data from various systems (e.g. CRM, billing platforms) on a daily, weekly, and monthly basis. • Ensure data integrity by performing routine validations, reconciliations, and checks. …/quarterly reports for senior leadership, including trend analyses, month-over-month comparisons, and variance explanations. • Support strategic initiatives and Lead or participate in special projects- providing data analysis, model validation, and performance tracking. • Conduct "deep dives" into specific issues and coordinate cross-departmental follow-up actions. KPI Monitoring & Analysis • Help define, monitor, and report on key performance More ❯

and optimisation framework, conducting reviews of client's processes and procedures, support regulatory or audit reviews, advising on TM technology, optimisation, and remediation programmes Define and lead on TM model optimisation, industry monitoring typology risk assessment methodology and overall control framework in building an effective Transaction Monitoring programme Leading and developing strong relationships with project stakeholders Supporting with planning … defining change governance, project management and business analyst background. Must demonstrate strong capability to define and articulate approach Technical Skills: (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 across rule designs, segment designs, technical design and processes (e.g NICE 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 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 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 More ❯

ve got up your sleeve It would be great if you also have some of the following skills: Experience with Data Build Tool (DBT) including building data models, tests, validation, and transformations. In-depth knowledge of sports betting markets, including odds calculation, betting types and market trends Previous experience in the online gaming or casino industry, with a strong More ❯

models in areas such as Automated Valuation Models (AVMs) and propensity modelling. You will take full ownership of the end-to-end data science lifecycle-from problem scoping to model deployment-while also setting technical standards, shaping strategy, and managing a team of three skilled data scientists. Key Responsibilities Manage a team of 3 data scientists, fostering a high … Set the vision and strategy for data science within the business, championing best practices and innovation Communicate complex technical concepts to both technical and non-technical stakeholders Guide experimentation, model validation, and continuous performance monitoring Contribute to long-term planning for the company's data science roadmap Tech Environment Strong emphasis on Python and cloud-based data science … tooling Experience with model deployment in production is essential Understanding of real estate or consumer behaviour data is a bonus, but not required About You Proven experience leading small data science teams in a commercial setting Strong expertise in machine learning, particularly with propensity modelling/AVM's Deep experience with end-to-end model development and deployment More ❯

Security Manage the security for the firms externally facing AI products, including ContractMatrix and other AI products currently in development by the firm. Establish and embed processes for secure model development, training, and deployment of AI products. Ensure that AI model behaviour in the firms AI products is continuously monitored for any anomalies and/or potential security … to understand complex AI models in order to give tailored security advice. Strong understanding of AI related data protection laws, and ethical frameworks. Familiarity with AI risk management tools, model validation, and regulatory reporting requirements. Excellent communication and stakeholder engagement skills, with the ability to bridge technical, and business perspectives. Confident in discussing complex AI models with product … or legal sector organisations. Certifications in AI ethics, data privacy (e.g., CIPP/E, CIPM), or risk management (e.g., CRISC). Experience with AI auditing, algorithmic impact assessments, or model governance platforms. Knowledge of legal technology tools and platforms (e.g., legal research AI, contract analytics, generative AI). Ability to lead cross-functional initiatives in a complex, multinational environment. More ❯

Manage the security for the firm's externally facing AI products, including ContractMatrix and other AI products currently in development by the firm. Establish and embed processes for secure model development, training, and deployment of AI products. Ensure that AI model behaviour in the firm's AI products is continuously monitored for any anomalies and/or potential … to understand complex AI models in order to give tailored security advice. Strong understanding of AI related data protection laws, and ethical frameworks. Familiarity with AI risk management tools, model validation, and regulatory reporting requirements. Excellent communication and stakeholder engagement skills, with the ability to bridge technical, and business perspectives. Confident in discussing complex AI models with product … or legal sector organisations. Certifications in AI ethics, data privacy (e.g., CIPP/E, CIPM), or risk management (e.g., CRISC). Experience with AI auditing, algorithmic impact assessments, or model governance platforms. Knowledge of legal technology tools and platforms (e.g., legal research AI, contract analytics, generative AI). Ability to lead cross-functional initiatives in a complex, multinational environment. More ❯

and optimisation framework, conducting reviews of client's processes and procedures, support regulatory or audit reviews, advising on TM technology, optimisation, and remediation programmes Define and lead on TM model optimisation, industry monitoring typology risk assessment methodology and overall control framework in building an effective Transaction Monitoring programme Leading and developing strong relationships with project stakeholders Supporting with planning … change 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 More ❯

requirements. Develop process maps and target operating models to enhance clarity and efficiency. Data analysis and definition, e.g. data-led insights, development ofdata dictionaries and data models. Supporting the validation of solutions delivered against acceptance criteria, through test planning, execution, coordination, etc. Partnering with Architects or Development teams to produce appropriate design specifications Continuously review and assess solution delivery More ❯

as a governance and architecture lead across multi-party AI initiatives. 4. Risk, Compliance & Responsible AI Ensure solutions are aligned with regulatory and compliance requirements (e.g., FINRA, SEC, GDPR, Model Risk Governance). Design solutions with embedded safeguards around transparency, explainability, auditability, and ethical AI usage. 5. Knowledge Development & Enablement Create reusable playbooks, frameworks, and GenAI solution kits specific … in both business and technology. Experience working in or with regulated financial environments and navigating security and compliance requirements. Preferred Qualifications Experience with retrieval augmented generation (RAG), fine-tuning, model evaluation, or deploying models in production environments. Understanding of financial risk modeling, model validation, or operational risk frameworks. Knowledge of regulatory frameworks such as DORA, SR More ❯

as a governance and architecture lead across multi-party AI initiatives. 4. Risk, Compliance & Responsible AI Ensure solutions are aligned with regulatory and compliance requirements (e.g., FINRA, SEC, GDPR, Model Risk Governance). Design solutions with embedded safeguards around transparency, explainability, auditability, and ethical AI usage. 5. Knowledge Development & Enablement Create reusable playbooks, frameworks, and GenAI solution kits specific … in both business and technology. Experience working in or with regulated financial environments and navigating security and compliance requirements. Preferred Qualifications Experience with retrieval augmented generation (RAG), fine-tuning, model evaluation, or deploying models in production environments. Understanding of financial risk modeling, model validation, or operational risk frameworks. Knowledge of regulatory frameworks such as DORA, SR More ❯

financial decisions across global markets. Responsibilities: Lead the 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 … of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Strong communication More ❯

financial decisions across global markets. Responsibilities: Lead the 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 … of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong coding skills in Python and SQL Strong communication More ❯

and workflow management of junior analysts to assist in reinsurance modelling and other areas of catastrophe modelling. Manage or contribute to various ad hoc exposure management projects such as model validation and emerging risk analysis. Stay abreast of exposure management best practice and emerging trends. Ad hoc reporting requests from the businesses. Peer review of other team members More ❯

asset classes, including equities, credit, FX, commodities, crypto, and derivatives. Write high-performance, clean, and optimized C++ code for distributed systems. Leverage Python and SQL to analyze and validate model inputs. Document methodologies to meet internal and external compliance standards. Who We're Looking For Education & Experience : M.S. or Ph.D. in Mathematics, Physical Sciences, or Engineering preferred, with More ❯

can drive value. In terms of more technical activities, the build of a computational twin involves a bunch of tasks common to all data science work such as EDA, model building, and model evaluation. In terms of other activities you'll do in the role: You'll be a leader within a cross-functional delivery team, working closely … A high 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. We regard the ability to develop new More ❯