16 of 16 Permanent Error Analysis Jobs in England

technology that connects the world. What You’ll Do: The Senior Flight Dynamics Mission Analyst (MA) will act as a cornerstone of the Mission Analysis function within the integrated Flight Dynamics (FD) team at Eutelsat Group. This team operates in a matrix‐style organization , spanning three technical verticals: Software … Mission Analysis, and Operations Engineering . This role reports to the Flight Dynamics & Mission Analysis Senior Manager and collaborates closely with FD peers across GEO and LEO programs to enable synergies in design, planning, and operations . Your responsibilities will include: Mission Analysis Leadership Perform full mission ...

imagery into quantitative insights that help us build better quantum processors. Combining classical image processing with deep learning, you'll develop end-to-end analysis capabilities that transform microscopy and metrology data into reliable measurements for process monitoring, scientific investigation and decision-making. The Role Working across our nanofabrication … materials teams, you’ll contribute to the development of computer vision and scientific image-analysis solutions, taking ownership of the development, validation and quality of the solutions you deliver. You’ll tackle problems spanning microscopic defect detection, segmentation and critical-dimension measurement, working with imagery from technologies including optical ...

comprehensive suite of test cases and evaluation benchmarks. Proactively identify potential model failure points, including edge cases, adversarial inputs, and sources of bias. Error Analysis & Failure Triage Conduct systematic error analysis to categorize model failures and identify underlying patterns. Triage defects, prioritize them based on severity ...

experiences, and operational controls Define validation approaches and success measures for AI and ML products, using appropriate offline and online metrics, experimentation, quality thresholds, error analysis, and business impact measures Use customer, campaign, and product data to identify opportunities, evaluate performance, make technical and product trade-offs … MLOps, observability, and reliability Experience defining evaluation and validation frameworks for AI or ML products, including offline metrics, online experimentation, human evaluation, quality thresholds, error analysis, and guardrails Experience building or productizing agentic systems, intelligent workflows, recommended systems, optimization systems, decision engines, or comparable AI-enabled platforms; able ...

architect calibrated LLM-as-a-judge pipelines, and build metrics that accurately capture multi-step agent performance under non-deterministic conditions. Your insights and error analyses will directly drive iterative improvements to our harness scaffolding, tool orchestration, and system safety guardrails. What you’ll do: Architect Evaluation Runtimes & Harnesses … latency, and variance across multi-step agentic systems. Design Experiments & Validate Results: Apply rigorous statistical methods—including hypothesis testing, confidence intervals, bootstrapping, and power analysis—to determine whether performance changes are true system improvements or stochastic noise. Build & Calibrate LLM-as-a-Judge Pipelines: Develop automated judging systems validated ...

possible, and communicating useful findings clearly. You will support senior R&D, Data Programme and AI colleagues while taking meaningful ownership of exploratory data analysis, data profiling, analytical prototyping and the measurement of data and AI products. You will join a small, hands‐on multidisciplinary team working collaboratively across … workspaces, build reproducible analyses and create clear visualisations and summaries for technical and business audiences. Form and test hypotheses; identify where further data, enrichment, analysis or modelling could create additional value for an R&D product or business question. Support the development and evaluation of baseline statistical and machine ...

supervised and unsupervised learning, including tree-based methods, generalized linear models, and/or deep learning, with strength in feature engineering, regularization, calibration, and error analysis Strong experimentation and statistics skills : designing and interpreting A/B tests, understanding bias/variance and statistical power, and applying causal ...

maintain the data pipelines behind your models, and own their deployment and reliability in production Build the evaluation frameworks, ground-truth sets and error analysis that prove an insight holds up before a customer sees it Quantify uncertainty and communicate confidence clearly, so the product never presents ...

decide where data and AI can genuinely improve services, then design, build and evaluate solutions that work in practice. Our work can include statistical analysis, machine learning, natural language processing, generative AI and agentic systems. Senior Data Scientists combine hands‐on technical delivery with the judgement needed to work … development. Exploring, cleaning and assessing data, including identifying limitations, quality problems and potential sources of bias. Implementing robust evaluations using appropriate metrics, test cases, error analysis and qualitative investigation. Considering performance beyond aggregate accuracy, including reliability, uncertainty, fairness, security, cost and the consequences of failure. Developing or evaluating ...

decide where data and AI can genuinely improve services, then design, build and evaluate solutions that work in practice. Our work can include statistical analysis, machine learning, natural language processing, generative AI and agentic systems. Senior Data Scientists combine hands‐on technical delivery with the judgement needed to work … development. Exploring, cleaning and assessing data, including identifying limitations, quality problems and potential sources of bias. Implementing robust evaluations using appropriate metrics, test cases, error analysis and qualitative investigation. Considering performance beyond aggregate accuracy, including reliability, uncertainty, fairness, security, cost and the consequences of failure. Developing or evaluating ...

testing data/ML pipelines, that are reliable, scalable and easily deployable in production environment. Productionising ML models and surrogates with clear validation, error analysis Exploring and manipulating 3D point‐cloud and mesh data, applying graph/geometry‐aware techniques where appropriate Working closely with simulation engineers ...

requires hands-on experience with Python and ML frameworks (PyTorch/TensorFlow), production ML pipelines, and GPU optimisation, with emphasis on rigorous evaluation and error analysis. #J-18808-Ljbffr ...

TypeScript.Practical experience with modern ML and LLM systems, including structured outputs, retrieval, tool use and evaluation.Strong understanding of experimental design, model limitations and systematic error analysis.Experience building and operating cloud services, including testing, observability and AI/ML operations.Ability to translate ambiguous requirements into clear technical approaches and reliable ...

Implement AT-TLS rules (digital certificate management). Configure and manage IPSEC policies (permit/deny rules, VPN- ipsec tunnels) Trace, Debug and Error Analysis Communicate regularly with technical, applications and operational staff to ensure Network connectivity and security (may involve some after hours and weekend work ...

support on reports developed to the business teams to ensure user adoption. Ensure accuracy, consistency, and timeliness of financial data, including data checking and error analysis. Being the point of contact for answering data related queries and clarifications. Identify opportunities to automate reporting and improve data processes. Skills & Experience ...

quality checks, lineage, provenance, observability, monitoring and change management within Fabric and Databricks workflows so data assets remain trusted over time. Conduct exploratory data analysis to surface patterns, gaps, anomalies and data-quality issues, and identify opportunities for analysis, modelling or product use. Develop, compare and validate appropriate … data-quality monitoring. Run EDA and model development that increases the value of priority data assets for client intelligence, opportunity identification, pricing, matter analysis and other high-value use cases. What Success Looks Like The Data Programme and R&D teams can use documented, quality-controlled data assets ...