76 to 100 of 164 Model Validation Jobs in the UK

to 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 More ❯

approach across multiple product lines. You'll play a key role in: Building and testing predictive models using Python and Databricks Exploring and integrating external data enrichments Contributing to model validation and peer code reviews Supporting pricing decisions that directly impact business growth and profitability Ideal candidate 2-8 years of experience in general insurance pricing (personal lines 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 ❯

is a unique chance to work alongside experienced private funds lawyers and innovators in a tech-forward environment. Navys is not just a better tool. It is a different model of how legal software should be built. You will be working on a product that completely reshapes the legal industry. As a Legal Associate, you will play a pivotal 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 ❯

derived tools robust to the heterogeneity of operating room environments. With customers all over the world operating rooms are often different which creates unique opportunities for problem solving and model design. Own the full model lifecycle including but not limited to data curation, model implementation, training, validation, deployment, and maintenance. Development within Proximie environment to enable … dynamic model training and performance evaluation while integrating with Proximies data lakes. Document solutions and contribute to internal knowledge sharing and capability building. Requirements PhD in a machine learning field such as computer science, data science, engineering, or a related field. Masters considered but PhD preferred. Minimum of 4 years hands-on experience in industry, developing and deploying AI More ❯

fertility testing and treatments Facilities : Fantastic site facilities including subsidised meals, free car parking and much more... The opportunity: In this role, we focus on the development, integration, and validation of dynamic numerical models, primarily using MATLAB and Simulink. We work with both the weapon effectors and the wider system components, in order to provide simulations of our products … lifecycle. Automation is a key part of our testing process, and we are hands on in putting continuous integration and verification processes in place, in conjunction with performing detailed model validation against experimental or field trial data. Ensuring quality standards are upheld is also important in our work, and all of our engineers participate in this through model … or other programming languages for system modelling and simulation. Knowledge of coding standards and peer review of coding changes Strong understanding of dynamic systems and numerical modelling. Familiarity with model-based design methodologies, the software development cycle, and systems engineering processes. Knowledge of scripting and automation (MATLAB scripts, Gitlab, Jenkins, or similar). Excellent problem-solving, analytical, and communication More ❯

re not here to say yes. You're here to ask: Are you sure? And sometimes: What the hell were you thinking? What youll actually be doing: Leading the Model Risk and Validation function in a fast-paced financial environment. Building frameworks that regulators respect and internal teams can actually follow. Validating complex models - credit risk, fraud, IFRS9 … them your entire personality. What we need from you: Youve led a team. A real one. Not just an intern and a weekly stand-up. 7+ years deep in model risk, validation, or building the things yourself. Ideally in the Financial Services sector. You can code. Python. SQL. Bonus points if youve wrestled with messy production code. Youve … do it properly. No fluff. No layers of red tape. Just a leadership role that actually leads. If that sounds more interesting than another year spent tweaking someone elses model, hit apply. Or dont. Just dont complain when someone else does. Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job function Job function Information 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. Who we're looking for: Experience in either a professional data science position or a quantitative academic field Strong python programming skills as evidenced … 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 ❯

in a quantitative discipline, with professional qualification such as CPA, CFA, FRM an added advantage Minimum 3 years of relevant working experience such as Product Control, Market Risk Management, Model Validation, with hands-on experience Broad understanding of financial products, knowledge of crypto products is a plus Proficient in Python and SQL Strong analytical skills, detailed oriented Hands 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 ❯

process. Development of quantitative models for the evaluation of complex structured deals, support originators/traders in the development and implementation of trading strategies incorporating such models. Development and validation of quantitative models for use in transaction valuation and risk measurement within the Commercial Risk. Risk data management - Ensure data in Risk systems are accurate, complete and accessible. Risk More ❯

process. Development of quantitative models for the evaluation of complex structured deals, support originators/traders in the development and implementation of trading strategies incorporating such models. Development and validation of quantitative models for use in transaction valuation and risk measurement within the Commercial Risk. Risk data management - Ensure data in Risk systems are accurate, complete and accessible. Risk More ❯

in taking the next steps in your career. Responsibilities: Experiment with various machine learning algorithms and techniques to identify the most suitable ones for given tasks. Conduct and validate model performance through comprehensive evaluation metrics. Analyze large datasets to extract actionable insights and trends. Implement machine learning models into production environments, ensuring scalability and reliability. Monitor and maintain the … related field. 3+ years' experience in implementing scalable ML systems into the production environment. Experience in all parts of the lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment. Proficiency in programming languages, including Python. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc. Experience developing Python APIs using tools More ❯

in advanced analytics, quantitative finance, and technology advisory for leading institutions across capital markets. The firm partners with clients to design and implement high-impact solutions in electronic trading, model development, and risk management. Leveraging deep domain expertise and cutting-edge technologies, it delivers tailored strategies that enhance performance, reduce complexity, and support regulatory alignment across the financial services … join a specialized consulting team tasked with designing and delivering quantitative trading and risk solutions for clients in global interest rate markets. This role involves leading engagements focused on model development, system architecture, and algorithmic design for pricing and electronic trading. Through deep collaboration with client stakeholders, the consultant will drive impactful outcomes by applying quantitative rigor and engineering … Translate technical outputs into actionable insights for both technical and non-technical stakeholders. Support project scoping, planning, and prioritization in alignment with client objectives. Assist clients in enhancing their model governance frameworks through technical review and effective challenge. Advise on best practices in model development, validation, and documentation across trading and risk domains. Guide clients in aligning 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 ❯

needs to be fluid in: Data warehousing and EMR (Hive, Pig, R, Python). Feature extraction, feature engineering and feature selection. Machine learning, causal inference, statistical algorithms and recommenders. Model evaluation, validation and deployment. Experimental design and testing. BASIC QUALIFICATIONS - 8+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience - 7+ More ❯

fertility testing and treatments Facilities : Fantastic site facilities including subsidised meals, free car parking and much more... The opportunity: In this role, we focus on the development, integration, and validation of dynamic numerical models, primarily using MATLAB and Simulink. We work with both the weapon effectors and the wider system components, in order to provide simulations of our products … lifecycle. Automation is a key part of our testing process, and we are hands on in putting continuous integration and verification processes in place, in conjunction with performing detailed model validation against experimental or field trial data. Ensuring quality standards are upheld is also important in our work, and all of our engineers participate in this through model … or other programming languages for system modelling and simulation. Knowledge of coding standards and peer review of coding changes Strong understanding of dynamic systems and numerical modelling. Familiarity with model-based design methodologies, the software development cycle, and systems engineering processes. Excellent problem-solving, analytical, and communication skills. Experience with version control tools (e.g., Git, EWM). Hands-on More ❯

with production-level code, version control (e.g., Git), and high-performance computing environments. Contributions to the development of systematic trading strategies that have been successfully deployed. Histories of rigorous model validation and performance analysis, with emphasis on avoiding overfitting and managing risk. Qualifications, Licenses And Academic Achievements: Ph.D. in a quantitative field highly preferred. Published research in top More ❯

with production-level code, version control (e.g., Git), and high-performance computing environments. Contributions to the development of systematic trading strategies that have been successfully deployed. Histories of rigorous model validation and performance analysis, with emphasis on avoiding overfitting and managing risk. Qualifications, Licenses And Academic Achievements: Ph.D. in a quantitative field highly preferred. Published research in top 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 ❯

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 ❯