9 of 9 Permanent Error Analysis Jobs in England

PAS, document management systems, and external data providers. Platform Monitoring : Determine requirements for specific alerts, set up alerts for various events and thresholds, utilise Datadog logs and dashboards for error analysis, and track DXC downtime while communicating updates to users. Platform Updates : Conduct a 3-way merge of updated code, validate new versions, and implement new features from More ❯

with a strong focus on code optimization, modular design, and efficiency. Demonstrable experience in developing, training, and deploying models using frameworks like PyTorch and TensorFlow. Strong understanding of data analysis, model evaluation, and error analysis to drive continuous model improvement. Excellent communication skills. Demonstratable commitment to continuous learning, staying current with state-of-the-art research and More ❯

TensorFlow. Demonstrated experience in building scalable, production-grade AI services and automated data pipelines with tools like Docker, Kubernetes, and cloud platforms (e.g., AWS). Strong understanding of data analysis, model evaluation, and error analysis to drive continuous model improvement. Proven ability to collaborate effectively in Agile/Scrum teams and contribute to cross-functional projects. Exceptional More ❯

TensorFlow. Demonstrated experience in building scalable, production-grade AI services and automated data pipelines with tools like Docker, Kubernetes, and cloud platforms (e.g., AWS). Strong understanding of data analysis, model evaluation, and error analysis to drive continuous model improvement. Proven ability to collaborate effectively in Agile/Scrum teams and contribute to cross-functional projects. Exceptional More ❯

compatible with GSK’s software stack, databases, and network infrastructure. Develop automated testing pipelines for post-quantum cryptographic algorithms to ensure security, efficiency, and scalability. Conduct performance benchmarking and error analysis of automated cryptographic transitions. Implement monitoring solutions to track the performance and reliability of automated cryptographic systems. Proactively identify and resolve issues related to cryptographic automation processes. More ❯

in training and inference. Collaborate with data engineers, software developers, and product teams to deliver AI/ML capabilities in production. Conduct rigorous model evaluations, A/B testing, error analysis, and performance tuning. Implement responsible AI principles and ensure model fairness, interpretability, and compliance. Explore and integrate open-source LLM models and fine-tuning strategies for specialized More ❯

tuning of machine learning and deep learning models. Contribute to scalable and reusable data pipelines using modern ML workflows. Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered More ❯

pipelines using frameworks such as PyTorch, TensorRT, ONNX, and TensorFlow Lite (cloud and edge) Collaborate with engineers and product stakeholders to integrate models into end-to-end systems Perform error analysis and iterate on models continuously in production environments What You'll Bring Master's degree with 3+ years of experience or Ph.D. with 0-2 years of … like PyTorch Familiarity with model optimization and inference acceleration tools (e.g., ONNX, TensorRT, OpenVINO, vLLM) Demonstrated ability to ship ML models in production settings, including performance monitoring and failure analysis Excellent communication skills and proven ability to collaborate across cross-functional teams Bonus: Prior experience with computer vision tasks (e.g., object detection, OCR, image classification) or retail/merchandising More ❯

its integrated as best as possible into their investment process, solve analytical problems that arise and optimise their efficiency using the risk tools (i.e. risk reporting, VaR and tracking error analysis, return attribution, stress testing, portfolio hedging, construction and optimisation etc). Besides this being a varied client engagement role in an enterprising environment that will allow you … Delta, Yieldbook, MSCI/Barra/Riskmetrics, Qontigo/Axioma, Factset etc. A creative approach and ability to present complex information in a clear and structured way. Excellent data analysis and problem skills. Must be customer focused and comfortable in such an environment with excellent written and verbal communication, besides having a consultative problem solving approach. Excellent career opportunity More ❯