1 to 25 of 28 Remote Model Validation Jobs in London

Services Team supports analytic and generative AI products for decisioning, analytics, and fraud and identity globally. As a Lead Data Scientist, you will use your coding expertise (Python, SAS), model risk management and Gen AI knowledge and experience, and analytic consulting skills to lead client and internal engagements for Experian's new global product launch and early client success … client base. Lead client analytic consulting engagements with financial services clients, including pre-sales and demos, training, and client success activities to maximize client value. Leverage Gen AI and model development tools to create and maintain new model document templates to help clients meet Model Risk Management regulatory requirements. Stay informed about regulatory changes, technological advancements, and … model risk management processes and controls to ensure the technology stack meets all compliance requirements. Research and integrate new data assets from different sources into Experian's ML and AI platform. Develop and assess analytic tools developed internally and externally. Gather feedback from internal and external clients to guide new product development, feature prioritisation, and product evolution of tools More ❯

strong engineering, and has opinions on building reliable, scalable systems. What you will be doing Drive the development of telematics features from mobile sensor data, including project design, modelling, validation, and deployment. Conduct deep dives into driving signals, develop hypotheses, and evaluate their predictive power for risk. Design technical solutions with clear trade-offs around performance, scalability, and maintainability. 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 ❯

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 ❯

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 ❯

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 ❯

Fine-tuning and optimizing models using tools like AlphaFold , RoseTTAFold , BioBERT , and DeepCell Integrating ML workflows with platforms such as Benchling , PubMed APIs , and internal R&D systems Supporting model validation, performance benchmarking, and regulatory documentation Key Technologies & Tools: ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose Data Sources: Genomic datasets More ❯

machine learning 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 price optimisation models Stay up-to-date on the most recent advances in AI and machine learning Requirements: PhD Degree in Computer Science More ❯

machine learning 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 More ❯

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 … a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion for solving complex problems using data and a continuous learning mindset Excellent communication and collaboration skills Full right More ❯

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 … a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion for solving complex problems using data and a continuous learning mindset Excellent communication and collaboration skills Full right More ❯

and employee development. Their risk and analytics functions are highly regarded, and the organisation is investing significantly in data-led decision making. THE ROLE You'll lead IFRS 9 model development within the mortgage's portfolio, with a focus on PD and LGD model design and implementation. This is a hands-on technical role, but also requires strong … Your key responsibilities will include: Leading the development of IFRS 9 PD and LGD models for the mortgage's portfolio. Managing and mentoring a team of two analysts. Supporting model monitoring, validation, and performance analysis. Contributing to stress testing and wider regulatory risk modelling as required. Collaborating with senior stakeholders to define modelling priorities and communicate insights effectively. More ❯

Your new company You will be joining an expanding consultancy focused on supporting innovation in the pharmaceutical and biotech industry. Its specialist research division is dedicated to solving complex biological problems through advanced statistical modelling and ML/AI. They More ❯

Your new company You will be joining an expanding consultancy focused on supporting innovation in the pharmaceutical and biotech industry. Its specialist research division is dedicated to solving complex biological problems through advanced statistical modelling and ML/AI. They More ❯

institutions and businesses which make the UK what it is. By encompassing a wide range of disciplines across a breadth of areas such as FRTB, Traded Risk, Conduct risk, Model Validation and Ops Risk we become immersed in our clients' organisations, applying sector knowledge and technology solutions to deliver the best possible outcomes and get it right first More ❯

institutions and businesses which make the UK what it is. By encompassing a wide range of disciplines across a breadth of areas such as FRTB, Traded Risk, Conduct risk, Model Validation and Ops Risk we become immersed in our clients' organisations, applying sector knowledge and technology solutions to deliver the best possible outcomes and get it right first More ❯

imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model serving, and system More ❯

imagery, and proprietary sourcesEnsure data quality, consistency, and reliability across heterogeneous data streams ML Development: Design and deploy models for pattern recognition, anomaly detection, and time-series forecastingContribute to model training, validation, and optimization processes Software Engineering: Develop production ML systems in Python on Google Cloud PlatformBuild and maintain APIs for data ingestion, model serving, and system More ❯

with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment (e.g. Podman, SageMaker, DSW pipelines) Version Control (Git … risk trends over financial years Exploratory Data Analysis (EDA): To spot early signals or risk clusters Desirable: Rank Aggregation/Ensemble Techniques: Understanding methods like Robust Rank Fusion (RRF) Model Explainability Tools: e.g. SHAP, LIME to support interpretability Experience with Model Monitoring & Drift Detection Experience in RegTech/FinCrime/Data-led Supervision Projects is a plus Additional More ❯

a range of people - both technical and non-technical - and a collaborative approach to getting things done. An interest inservice design and introduction, including things like support models, service validation, and process mapping (e.g., using Visio). Some exposure to tools likeServiceNowandJira, and an awareness of ways of working such asAgile,DevOps, orITIL. Additional information We're always looking More ❯

to uncover insights, test hypotheses, and identify features that drive business value Work on all parts of the data science workflow: from data cleaning and exploratory analysis to offline model benchmarking and validation Collaborate with marketers to reduce manual overhead in campaign management while improving ad efficiency and profitability Improve our ad feed infrastructure to ensure product attributes … pricing and availability are optimised for campaign performance Contribute as needed to product data initiatives (e.g. classification, deduplication), especially where they impact ad quality or model input 3+ years of experience building and deploying ML models in production Strong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluation Deep understanding of … the data science process-comfortable with exploratory analysis, statistical testing, and model comparison techniques Experience with structured prediction problems (e.g. regression, classification, ranking) using real-world, often messy data Familiarity with advertising systems (Google Shopping, PMAX, etc.) and marketing metrics like ROAS, profit, and conversion is a strong advantage Experience productionising ML models-setting up training pipelines, versioning, monitoring More ❯