51 to 75 of 82 Statistical Modelling Jobs in England

design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement … accuracy. Requirements: Proven experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master ...

design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Act as a technical lead within project teams, mentoring … model accuracy. Proven experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master ...

Ensure compliance with security, performance, and reliability standards across multi-cloud platforms. Required Skills & Experience: Data Science Background: Strong foundation in data science principles, statistical modeling, and machine learning algorithms. Consulting Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience ...

Scientist Contractor £500-600pd Outside IR35 3 months We are working with a leading consultancy that is looking for an experienced Marketing Mix Modelling (MMM) Data Scientist to join on a contract basis. This role will focus on delivering robust marketing effectiveness and ROI insights for high-profile … Design and build Marketing Mix Models to measure marketing effectiveness and ROI Analyse large, complex datasets covering media spend, sales, and external factors Apply statistical and econometric techniques to model impact and attribution Use Python and/or R to develop, test, and deploy models Use SQL to extract ...

formats. You'll be at the heart of decision-making and continuous improvement, using your expertise in data science, retail operations, and statistical modelling to deliver meaningful, data-backed change directly into our stores. You will manage data collection methodologies, conduct advanced analyses, and ensure the integrity … Sourcing and Integrity: Working with cross-functional teams to identify, capture, and ensure the high integrity of data necessary for model development, including conducting statistical analysis on task measurement outputs. Model Implementation Support: Providing analytical support and insight during the implementation of new scheduling systems, ensuring models are correctly ...

Quantitative Analyst (or similar), delivering pricing and risk metrics for complex derivatives and structured products Excellent understanding of a variety of mathematical and statistical models, stochastic calculus in particular, and their use in finance Master's Degree or PhD qualification within science, computing, mathematics or other quantitative subject Familiarity ...

data engineering teams to maintain robust data infrastructure. Analytics and Insights: Design and oversee complex data analysis projects to derive actionable insights. Utilize statistical methods, machine learning models, and advanced analytics techniques. Present findings and recommendations to stakeholders through reports, dashboards, and presentations. Collaboration and Communication: Collaborate with various … Adobe Analytics, ContentSquare), data analytics tools/languages (SQL, Python, R, SAS), and data visualization platforms (e.g., Tableau, Power BI). Strong understanding of statistical methods, machine learning, data mining techniques, data warehousing solutions, big data technologies, and data engineering concepts. Exceptional leadership, team management, and communication skills, with ...

working cross-functionally with Marketing and Product teams to turn insight into commercial impact. Responsibilities include Owning customer analytics projects such as segmentation, churn modelling, LTV, and lifecycle optimisation Designing and analysing A/B and multivariate tests to shape acquisition and retention strategies Using SQL and dashboarding tools … outputs into strategic recommendations and tell clear data stories Experience designing or analysing A/B testing and customer lifecycle analytics Python skills for statistical modelling or automation are an advantage This role offers a hybrid setup (typically two days per week in the London office), a base ...

from SDR platforms Build RF signal analysis and visualisation tools Design RF data-processing pipelines accounting for real-world hardware effects Develop ML and statistical models for RF classification and detection Prototype batch and real-time processing systems in Python and integrate with GNU Radio or C++ backends Support ...

technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics or personal projects related to football data. Knowledge of advanced football metrics (possession ...

Strong SQL, Excel and data manipulation skills with experience in BI tools like Tableau or Power BI Programming experience in R or Python for statistical analysis and data modelling Experience with relational databases (Oracle, SQL Server) and database design Exposure to VBA, Bash scripting or other automation tools … Knowledge of financial services data, risk modelling or regulatory reporting is a plus Familiarity with cloud platforms like AWS or Azure for data analytics is desirable Comfortable working across multiple stakeholders and presenting insights at executive level Strong communication skills and ability to translate complex data into clear recommendations ...

passionate about using advanced data science to drive real-world impact in sport, this is the role for you. Key Responsibilities Develop and apply statistical models and algorithms to analyse player performance, match outcomes, and tactical insights Collect, clean, and process football-related data from diverse sources Build clear … experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such ...

. Hands on experience with a modern deep learning framework, preferably PyTorch. Strong theoretical understanding of machine learning principles, including deep learning and classical statistical models. Knowledge of the inner workings of LLMs and VLMs, the ability to gut them and work with them past just surface-level functionality. ...

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 ...

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 ...

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 ...

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. ...

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. ...

focused environment. Proficiency in SQL and Python or R, with experience using BI tools such as Power BI, Tableau, or Looker Studio. Confident with statistical analysis, predictive modelling, and translating insights into clear recommendations. Comfortable working in a fast-paced setting where collaboration and initiative are key. Interview ...

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 ...

sustainable subscriber growth. THE TEAM You'll join the newly established Marketing Analytics function; a specialist group focused on advanced measurement, marketing mix modelling, experimentation, and campaign performance evaluation. Sitting within the wider Analytics organisation (which includes content analytics, local analytics, and subscriber growth), this team partners closely with … influence investment decisions. Contributing to the development of measurement methodologies across a scaling analytics organisation. SKILLS & EXPERIENCE REQUIRED Essential: Proven experience in Marketing Mix Modelling and marketing effectiveness frameworks. Strong SQL skills (high bar - candidates must be comfortable scoring 10-11 out of 15 on SQL assessments). Hands ...

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 ...