1 to 25 of 41 Bayesian Methods Jobs in the UK excluding London

understanding of statistical modelling/ML techniques Experience with Regression based models applied to the context of MMM modelling Solid experience with Probabilistic Programming and Bayesian Methods Be an expert in mining large & very complex data sets using SQL and Spark Have in depth understanding of statistical modelling techniques and their mathematical foundations, Have a good More ❯

Initial 12 month contract + potential to extend long-term due to 3/4 year project scope. Start Date: ASAP We have an excellent opportunity for a Bayesian Data Scientist to join a leading FMCG Brand, Initial 12 month contract + opportunity to extend long-term. This is an exciting opportunity to join a high-performing … Data Science team focused on advancing marketing effectiveness through advanced econometric modelling—including Bayesian Marketing Mix Modelling (MMM), Multi-Touch Attribution (MTA), and data-driven optimization strategies. Key Responsibilities Lead and manage data workflows: data extraction, transformation, validation, and exploratory analysis to ensure modelling-readiness. Build and refine Bayesian MMM models that capture the … test models, identifying opportunities for improvement and ensuring robustness, interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. More ❯

is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming and Bayesian methods Good working knowledge of cloud-based data science frameworks. This is a 6 month contract position which provides a daily rate of £688 (Inside IR35). In terms of More ❯

one or more cloud computing platforms (Azure - preferred, AWS, GCP). Understanding of the whole ML lifecycle and experience with MLOps/DataOps. Experience with Probabilistic Graphical Modelling (Bayesian Networks, Markov Random Fields, Factor Graphs, ...) Strong problem-solving skills and attention to detail. Good communication skills, fluent English. If interested, please get in touch via contact More ❯

validation Confident working across teams and taking ownership of delivery Strong communication and problem-solving skills Experience in demand forecasting or operations research Familiarity with Bayesian methods, Monte Carlo simulations, or reinforcement learning Exposure to high-scale SaaS or B2C products Why Apply? Build forecasting systems powering global commercial strategies Collaborate with a world-class data More ❯

Science Consultant. The successful candidate will be a key player in developing and implementing advanced pricing and marketing optimization models, leveraging Bayesian statistics, causal inference, econometric methods, and Python to deliver impactful insights in the CPG domain. Responsibilities Design and build sophisticated pricing and marketing optimization models using Bayesian, causal inference, and econometric … Mathematics) Minimum of 5 years of experience in a data science role focused on pricing and marketing optimization Proven expertise in Bayesian, causal inference, and econometric methods Strong proficiency in Python and experience deploying models to production Experience with cloud platforms, preferably Azure, Databricks, MLFlow, Airflow, and Plotly Dash Nice to have PhD in a relevant More ❯

The successful candidate will be a key player in developing and implementing advanced pricing and marketing optimization models, leveraging expertise in Bayesian statistics, causal inference, econometric methods, and proficiency in Python, specifically in the CPG (Consumer Packaged Goods) domain. Responsibilities Design and build sophisticated pricing and marketing optimization models using Bayesian, causal inference … of 5 years of experience in a data science role with a focus on pricing and marketing optimization Proven expertise in Bayesian, causal inference, and econometric methods Strong proficiency in Python and experience in taking models to production Experience with cloud computing platforms, preferably Azure, and tools such as Databricks, MLFlow, Airflow, and Plotly Dash Nice More ❯

Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of A/B tests. • Familiarity with Bayesian statistics, especially for hypothesis testing. Extra points for good knowledge of Bayesian programming (PyMC3, etc). • Experience with application of optimization theory or reinforcement learning More ❯

for the LGBTQ+ business community. Please do not contact the recruiter directly. Summary Understand complex and critical business problems, formulate integrated analytical approaches to mine data sources, employ statistical methods and machine learning algorithms to help solve unmet medical needs, discover actionable insights, and automate processes to reduce effort and time for repeated use. Manage the implementation and adherence … science, biostatistics, or a related quantitative field (or equivalent). Over 3 years of experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge of statistical methods such as survival analysis, machine learning, meta-analysis, mixed-effects modeling, Bayesian methods, and variable selection techniques. Proficiency in R and Python, with experience in More ❯

methodologies Self-motivated, enthusiastic, and organised, with excellent attention to detail Proactive and delivers to timescales Attention to detail in creating documentation The ability to conduct descriptive statistics, Bayesian statistics, Inferential statistics . click apply for full job details More ❯

teams to design, implement, and optimize data pipelines and predictive models that inform trading decisions and enhance operational efficiency. RESPONSIBILITIES: Primary Focus: Probabilistic Weather Modelling: Research and prototype probabilistic methods (Bayesian inference, state-space filtering, change-detection tests, etc.) that flag when fresh weather guidance materially diverges from prior outlooks. Continuous Development and Improvement: Calibrate confidence … of a degree in Statistics, Applied Maths, Physics or related field. Minimum of 2 years working in a Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). More ❯

BigQuery for data modelling and warehousing Some examples of our data science work can be found in our engineering blog: Image catergorisation Moving to a A(/B) Bayesian World Scoring adverts quickly but fairly Life Cycle of Our Package Uplift Model What … We're Looking For Experience delivering data-science solutions in a commercial or research (e.g. PhD) environment A strong understanding of Data Science techniques, including ML algorithms and statistical methods Proficient in building ML pipelines with Python An enthusiasm for engaging with non-technical stakeholders and establishing scientific rigour in teams Experience collaborating on Data Science projects and working More ❯

Who You Are - Proven track record leveraging machine learning to solve real-world problems; Expertise in one or more of the following: generative models, language models, computer vision, bayesian inference, causal reasoning & inference, transfer & multi-task learning, diffusion models, graph neural networks, active learning; Experience writing production-quality code with modern machine learning frameworks such as PyTorch … Experience in cell health and rejuvenation-related research area; Experience with identification and assessment of drug targets and/or therapeutic compounds; Experience in the application of machine learning methods to biological data, including genomics, transcriptomics, epigenetics, proteomics, and imaging; Track record in open-source software development, e.g., demonstrated by high-impact GitHub repository; Track record of high-caliber More ❯

Skills and Experience Strong academic background, with a degree in Computer Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with More ❯

Skills and Experience Strong academic background, with a degree in Computer Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with More ❯

Skills and Experience Strong academic background, with a degree in Computer Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with More ❯

magnetometry technology that will solve pressing challenges in aeronautical positioning and navigation, geophysical surveying, and magnetic anomaly detection. A key focus of the role will be developing and implementing methods for removing magnetic and/or vibrational noise induced by the platform on which the quantum sensor is mounted. The algorithms, signal processing, automation, and data analytics you develop … analysis and develop platform and environmental noise compensation techniques that enable high quality magnetic- and gravity-aided navigation using state-of-the-art digital signal processing and machine learning methods; Use data analytics to translate quantum sensor data streams into capabilities that solve pressing challenges for current and prospective end-users and customers; Work closely with other Research and … and/or platform motional characterisation and management; magnetic and/or vibrational signal denoising; quantum sensing and/or other sensing technologies. Knowledge and experience of machine learning methods to time series data including generative modelling. Contributing to a software system architecture with multiple components developed by different teams, adhering to best-practice software development precepts. Experience communicating More ❯

please apply. Responsibilities Design, build and scale supervised ML models for active learning and Bayesian Optimization of materials synthesis and performance Implement best practices and innovate methods for uncertainty quantification Combine datasets of multiple fidelities and sources to power data-driven materials discovery Work with the computational team to identify materials design pathways that target desired … conferences, and developing relationships with key opinion leaders Report findings to stakeholders and leadership in written reports and verbal presentations. Qualifications Experience with uncertainty quantification, active learning and Bayesian Optimization Experience implementing, evaluating, and hyperparameter tuning small and large supervised models in a Bayesian Optimization context (Gaussian processes, Bayesian Neural Networks More ❯

machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with Azure: Azure Databases, Azure Databricks Proficient use of VBA's Apply for this job #J-18808-Ljbffr More ❯

machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with Azure: Azure Databases, Azure Databricks Proficient use of VBA's Please note due to the large volume of applications we receive More ❯

approaches when the task calls for it Values communication, empathy, and teamwork Real-world industry experience is strongly preferred, as we’re looking for candidates who can apply advanced methods to practical, high-impact problems and navigate the complexity of real operational environments. We welcome applications from both mid-level and senior professionals; however, due to the complexity of … chance to learn and work with: Physical and empirical modelling of complex systems Machine learning for prediction and inference Optimisation and real-time decision engines Bayesian methods and uncertainty quantification Collaborative software development and production deployment What We Offer A truly inclusive, supportive team culture Flexible working hours and remote-first environment Competitive salary with performance More ❯

of our technology solutions. Knowledge, Experience and Qualifications Essential You have experience with some modelling paradigms and techniques such as active learning, transfer learning, agent-based modelling, optimisation, Bayesian inference, entity extraction/resolution, spatio-temporal modelling. Enjoy developing models from first principles and are unbiased in your choice of modelling techniques. Experience across some of the More ❯

management Key Experience: Strong academic background with a minimum 2:1 Degree in Computer Science (or similar) Strong numerical background with a knowledge of key statistical principles – eg Bayesian and frequentist statistics Experience with multiple programming languages including SQL and Python Familiarity with large language models Understanding of ML algorithms This is an excellent opportunity for a More ❯

sensing, or statistical modelling 3+ years of experience in climate risk, catastrophe, or related modelling domains Bonus Experience Expertise in exposure and vulnerability within catastrophe models Background in Bayesian statistics, Extreme Value Theory, or uncertainty quantification Knowledge of machine learning techniques for climate risk Familiarity with cloud computing (AWS, GCP) ? Hybrid working (3 days/week on More ❯

For A 2:1 or higher degree in Computer Science, Data Science, AI, or a related discipline. Strong numerical and statistical knowledge (e.g. Bayesian/frequentist methods, probability distributions). Solid understanding of machine learning algorithms (e.g. linear/logistic regression, random forests, neural networks, time series models). Experience with multiple programming languages — with Python More ❯