76 to 96 of 96 Statistical Modelling Jobs in the UK excluding London

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

Vertex AI (or equivalent cloud ML platforms). Solid software engineering fundamentals: APIs, Docker, CI/CD, and Git. Strong understanding of deep learning, statistical modelling, and optimisation techniques. Nice to Have Experience with agentic design patterns (e.g. ReAct, Chain-of-Thought, tool use). Familiarity with ...

proficiency in SQL for querying, aggregating, and analyzing large datasets. Strong programming skills in Python (including libraries like Pandas, NumPy) for data manipulation and statistical analysis. Proven experience working with and processing large-scale, complex datasets stored in Hadoop or similar distributed file systems/data lakes. Demonstrable experience … Money Laundering (AML), or Sanctions compliance data analysis. Familiarity with cloud data warehousing solutions (e.g., Snowflake, Google BigQuery, AWS Redshift). Experience with advanced statistical modeling or machine learning techniques applied to financial data. About Barclays Barclays is a British universal bank, diversified by business, by customer type ...

hands-on role for someone who enjoys technical depth, variety, and ownership, and who is comfortable applying the right techniques to each problem - from statistical analysis through to machine learning and deep learning models. You’ll join a small, high-calibre team that values autonomy, flexibility and technical excellence. … complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. Working with large, structured ...

predict outcomes! Operations research: handling constraints, finding optimal arrangements for fastest packing. Stochastic simulation: accounting for variability in machine speeds and conveyor setups. Techniques: statistical simulation, stochastic modeling, linear optimization. Tools & Platforms Expertise: Databricks for data workflows. GitHub for CI/CD and version control. Package management for reproducibility. ...

role you must have the following essential skills & experience: Key Skills & Experience Model development: Work collaboratively with actuarial analysts to develop machine learning and statistical models to predict outcomes, related to pension schemes, such as life expectancy, default risk, or investment returns. Identify appropriate machine learning algorithms and apply … them to enhance predictions, automate decision-making processes, and improve client offerings. Machine Learning Operations: Responsible for designing, deploying, maintaining and refining statistical and machine learning models using Azure ML. Optimize model performance and computational efficiency. Ensure that applications run smoothly and handle large-scare data efficiently. Implement ...

deliver actionable insights across the network of charging points Analyse customer behaviour, usage patterns, and operational data to inform strategy and growth Build statistical models for segmentation, regression, predictive modelling, and forecasting Support pricing and revenue optimisation initiatives, including dynamic pricing strategies Query and process large datasets coming … into clear recommendations for non-technical stakeholders What You'll Need: Strong SQL and Python skills; experience in AWS environments is a plus Solid statistical analysis background (segmentation, regression, forecasting) Hands-on, adaptable, and comfortable in a smaller, fast-moving team environment Excellent communication skills and ability to take ...

performance, and timing jitter. You will also model RF front-end behaviour, improving signal integrity and inference accuracy, and apply machine learning and statistical models for classification, anomaly detection, and emitter identification. You will prototype real-time and batch-processing systems using Python (NumPy, SciPy, PyTorch) and integrate them … will have strong Python proficiency for data analysis and prototyping, a solid understanding of digital signal processing (FFT, filtering, modulation, correlation, resampling, and noise modelling), and familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR. A practical understanding of RF hardware chains - from antenna through filters ...

cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna → filters → mixers ...

cyclic spectra, EVM, autocorrelation, constellation tracking, etc.) Designing RF data-processing pipelines built around practical hardware constraints (bandwidth, ADC limits, gain stages, timing jitter) Modelling RF front-end behaviour (filters, mixers, LOs, AGC, noise figure) to improve signal integrity and inference accuracy Developing ML and statistical models … Python proficiency for RF data analysis and prototyping (NumPy, SciPy, matplotlib, scikit-learn, PyTorch) Solid understanding of DSP fundamentals (FFT, filtering, modulation, correlation, noise modelling, resampling) Familiarity with SDR frameworks such as GNU Radio, SDRangel, osmoSDR, or SoapySDR Practical understanding of RF hardware chains (antenna ? filters ? mixers ...

succeed Not the classic "predictive modeling" skillset Data Science skillset Needed skills: Exploration vs. exploitation mindset Advanced Optimization Skills: Expertise in linear optimization and statistical optimization for systems. Strong background in modeling and solving problems involving variability and constraints. Ability to search optimal recipe space within a model. Build … predict outcomes. Operations research: handling constraints, finding optimal arrangements for fastest packing. Stochastic simulation: accounting for variability in machine speeds and conveyor setups. Techniques: statistical simulation, stochastic modeling, linear optimization. Industry Experience: Exposure to renewable energy, manufacturing, electronic systems or distribution (Retail/Food). Tools & Platforms: Databricks ...

Machine Learning Engineer or Senior Machine Learning Engineer to design, build and maintain the frameworks, tooling and packages that support high quality modelling and analytical workflows. You will play a key role in enabling fast, reliable and scalable delivery of ML driven solutions across the business. The environment … collaborative, fast paced and engineering focused, with a strong emphasis on high standards, automation and continuous improvement. Role: Develop and operationalise Python based modelling tools and frameworks that support the full analytical lifecycle Create tools, APIs and processes that enable seamless, efficient and controlled deployment of ML and statistical ...

clients within the Financial Services space and more. This role offers the chance to work on a really diverse range of projects, from scorecard modelling to AI integration, and could really see you take your career to the next level. THE ROLE This role would see you work with … range of clients on projects including: Re-developing and enhancing statistical models, including but not limited scorecards, affordability models, forecasting models, to drive insight into the customer journey and enhance business performance Provide wider ad hoc analysis and insight into customer trends and monitor the ongoing performance of credit ...