151 to 175 of 187 Statistical Modelling Jobs in the UK

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 ...

Property Finder, driving data strategy, and delivering impactful AI solutions. Key Responsibilities: Design and implement advanced predictive and optimization models, leveraging classical ML/Statistical model, deep learning models, and modern AI techniques. Drive applied innovation in Large Language Models (LLMs), Generative AI, and Agentic AI systems, exploring … 3+ years in Data Science or MLE roles and foundational MLOps practices. Technical Skills: Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with ...

Property Finder, driving data strategy, and delivering impactful AI solutions. Key Responsibilities: Design and implement advanced predictive and optimization models, leveraging classical ML/Statistical model, deep learning models, and modern AI techniques. Drive applied innovation in Large Language Models (LLMs), Generative AI, and Agentic AI systems, exploring … 3+ years in Data Science or MLE roles and foundational MLOps practices. Technical Skills: Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with ...

Property Finder, driving data strategy, and delivering impactful AI solutions. Key Responsibilities: Design and implement advanced predictive and optimization models, leveraging classical ML/Statistical model, deep learning models, and modern AI techniques. Drive applied innovation in Large Language Models (LLMs), Generative AI, and Agentic AI systems, exploring … 3+ years in Data Science or MLE roles and foundational MLOps practices. Technical Skills: Working knowledge of advanced predictive modeling, optimization, scenario analysis, and statistical methodologies. Strong grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with ...

influence strategic decision-making across the company. Key Responsibilities: Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such … data scientists or leading end-to-end ML projects independently. Technical Skills: Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling. Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness. Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning ...

influence strategic decision-making across the company. Key Responsibilities: Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such … data scientists or leading end-to-end ML projects independently. Technical Skills: Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling. Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness. Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning ...

influence strategic decision-making across the company. Key Responsibilities: Lead the design and implementation of complex predictive and optimization models using classical ML/statistical methods, deep learning architectures, and generative techniques. Drive innovation in Large Language Models (LLMs), Generative AI, and Agentic AI—pioneering new applications such … data scientists or leading end-to-end ML projects independently. Technical Skills: Expertise in supervised/unsupervised learning, deep learning (CNNs, RNNs, transformers), and statistical modeling. Strong foundation in scenario modeling, optimization, and evaluation metrics for performance and fairness. Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning ...

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 ...

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 ...

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 ...

Location: London Experience: 12 to 18 years CTC: 4000 TO 4500 US Dollars Job Requirements: 12 years of experience manipulating data sets and building statistical and machine learning models. Masters or Ph D in Statistics, Mathematics, Computer Science, or another quantitative field - Fluent English (written/spoken) Generative … studies Transferring data into a new format to make it more appropriate for analysis Build tools to automate data collection Compare and analyze provided statistical information to identify patterns, relationships, and problems Define and utilize statistical methods to solve industry-specific problems in varying fields, such as economics ...

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 ...

learning, and the chance to make a difference. About the Role As a Data Scientist, you’ll work end-to-end across data pipelines, modelling, and insights — helping the business make smarter decisions every day. You’ll collaborate with product, engineering and senior stakeholders, with full support from … team. If you love solving problems, asking questions, and building useful things with data, this role is for you. Key Responsibilities ✅ Build predictive and statistical models using Python ✅ Develop end-to-end data pipelines and automated workflows ✅ Analyse behavioural, financial or operational datasets ✅ Create dashboards and visualisations ...

learning, and the chance to make a difference. About the Role As a Data Scientist, you’ll work end-to-end across data pipelines, modelling, and insights — helping the business make smarter decisions every day. You’ll collaborate with product, engineering and senior stakeholders, with full support from … team. If you love solving problems, asking questions, and building useful things with data, this role is for you. Key Responsibilities ✅ Build predictive and statistical models using Python ✅ Develop end-to-end data pipelines and automated workflows ✅ Analyse behavioural, financial or operational datasets ✅ Create dashboards and visualisations ...

learning, and the chance to make a difference. About the Role As a Data Scientist, you'll work end-to-end across data pipelines, modelling, and insights — helping the business make smarter decisions every day. You'll collaborate with product, engineering and senior stakeholders, with full support from … team. If you love solving problems, asking questions, and building useful things with data, this role is for you. Key Responsibilities Build predictive and statistical models using Python Develop end-to-end data pipelines and automated workflows Analyse behavioural, financial or operational datasets Create dashboards and visualisations ...

Familiarity with syndicated data sources (e.g., Nielsen, IRI/Circana, Kantar) and retailer point-of-sale data. Preferred Skills Analytics Proficiency: Strong grasp of statistical concepts (Regression, Clustering, Elasticity). Ability to guide data scientists on modeling approaches. Tools: Advanced proficiency in Excel, Powerpoint is non-negotiable. Experience with … developer, but must have some understanding of the code logic and capabilities). Functional knowledge (prefer some hands-on experience) of data analytics, statistical models (MMM, Price-Promotions etc.), retail audit data (e.g. Nielsen, IRI) is strongly desirable. Soft Skills: Exceptional storytelling and presentation skills. Ability to manage ambiguity ...

Familiarity with syndicated data sources (e.g., Nielsen, IRI/Circana, Kantar) and retailer point-of-sale data. Preferred Skills Analytics Proficiency: Strong grasp of statistical concepts (Regression, Clustering, Elasticity). Ability to guide data scientists on modeling approaches. Tools: Advanced proficiency in Excel, Powerpoint is non-negotiable. Experience with … developer, but must have some understanding of the code logic and capabilities). Functional knowledge (prefer some hands-on experience) of data analytics, statistical models (MMM, Price-Promotions etc.), retail audit data (e.g. Nielsen, IRI) is strongly desirable. Soft Skills: Exceptional storytelling and presentation skills. Ability to manage ambiguity ...

data manipulation and engineering. A genuine interest in data science and a drive to expand your skillset into predictive analytics, machine learning, or statistical modeling. Strong analytical and problem-solving skills with a passion for optimising workflows. Excellent communication and teamwork abilities to thrive in a dynamic consultancy environment. … Data modelling experience and understanding of the Kimball methodology Desirable Expertise: DP-600 – Fabric Analytics Engineer Associate PL-300 – Power BI Data Analyst Associate DP-700 - Fabric Data Engineer Associate Responsibilities: On a daily basis your varied role will include, but will not be limited to: Design, build ...

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 ...

influence strategy, game-economy design, and commercial performance. As a Senior Data Scientist, you’ll work across player behaviour, game-economy optimisation, and predictive modelling, helping to scale automated decision systems across the organisation. Your work will be highly visible, with frequent opportunities to present directly to senior leadership. … strategic decision-making. Collaborate across data science, engineering, product, and commercial teams to deliver end-to-end solutions. Improving player retention and engagement using statistical modelling. Enhancing automated decision systems across the gaming ecosystem. Evaluating reward effectiveness and game-economy balance. Driving experimentation and structured multivariate testing across product ...

approach. You will join Central Test's Research & Development department, working alongside occupational psychologists, psychometricians, data scientists, and researchers, contributing to the creation and statistical validation of psychometric tests and HR tools. Your role You will contribute to the development, revision and validation of our psychometric tools. Your main … responsibilities will include: Data collection, analysis, quality control, and statistical validation of psychological models and HR frameworks Keeping up to date with industry advancements and applying these to our processes Quality control of Central Test's platform, including standardisation and scoring Contribution to technical platform conception and redesigns, such ...

approach. You will join Central Test’s Research & Development department , working alongside occupational psychologists, psychometricians, data scientists, and researchers, contributing to the creation and statistical validation of psychometric tests and HR tools. 🎯 Your role You will contribute to the development, revision and validation of our psychometric tools. Your main … responsibilities will include: Data collection, analysis, quality control, and statistical validation of psychological models and HR frameworks Keeping up to date with industry advancements and applying these to our processes Quality control of Central Test’s platform, including standardisation and scoring Contribution to technical platform conception and redesigns , such ...

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 ...