26 to 50 of 167 Bayesian Methods Jobs in the UK

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 ❯

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 ❯

sophisticated pricing algorithms which would enable companies in the entertainment industry to significantly increase profit margins. You'll use a raft of different techniques from timeseries analysis to bayesian statistics, reinforcement learning & Monte Carlo Simulations. Your Experience : You'll likely come from a strong quantitative degree background in Science or Maths and have worked 2-4 years 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 play a key role in developing and implementing advanced pricing and marketing optimization models, leveraging expertise in Bayesian statistics, causal inference, econometric methods, and proficiency in Python to deliver impactful insights in the CPG domain. Responsibilities Design and build sophisticated pricing and marketing optimization models using Bayesian, causal inference … Computer Science, Statistics, Physics, Mathematics) Minimum 5 years of experience in data science, focusing on pricing and marketing optimization Expertise in Bayesian, causal inference, and econometric methods Strong proficiency in Python and experience deploying models Experience with cloud platforms, preferably Azure, Databricks, MLFlow, Airflow, and Plotly Dash Nice to Have PhD in a relevant field Experience 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 ❯

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 ❯

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 ❯

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 ❯

mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an More ❯

Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the implementation and adherence to the overall data lifecycle of enterprise data from data acquisition or … biostatistics, or other quantitative field (or equivalent). More than 3 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net More ❯

a data scientist, quantitative researcher, quantitative analyst or another relevant roleDegree in Applied Mathematics, Computer Science, Financial Engineering, Technology or EngineeringKnowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methodsExperience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models 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 ❯

deep-learning frameworks (e.g., TensorFlow, PyTorch). High mathematical competence and proficiency in statistics. Solid understanding of data science techniques such as supervised/unsupervised learning, cross-validation, Bayesian inference, time-series analysis, NLP, SQL, and API development. Ability to develop new algorithms is a fundamental skill. Leadership mindset focused on team growth, mentorship, and fostering a 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 ❯

analytics or media environments. 💡 Bonus Points For: Experience working with large datasets or cloud platforms (e.g. GCP/Big Query). Exposure to advanced analytics approaches such as Bayesian or non-regression models. Familiarity with marketing measurement tools or platforms (e.g. Robyn, Meridian). Data viz skills in Power BI, Tableau, or Data Studio. A background in More ❯

analytics or media environments. 💡 Bonus Points For: Experience working with large datasets or cloud platforms (e.g. GCP/Big Query). Exposure to advanced analytics approaches such as Bayesian or non-regression models. Familiarity with marketing measurement tools or platforms (e.g. Robyn, Meridian). Data viz skills in Power BI, Tableau, or Data Studio. A background in More ❯

health economics, including the conceptualization and development of systematic literature reviews and network meta-analyses (8+ years, ideally in a consultancy environment) Strong basis in fundamental statistical concepts and methods and familiarity with techniques such as the development of predictive equations, survival analysis (including parametric methods), longitudinal data analysis, meta-analysis, mixed treatment comparison, and other hierarchical analysis … techniques Familiarity with machine learning techniques and Bayesian statistics is a plus Strong communication (spoken and written) and problem-solving skills, and an ability to learn quickly Ability to communicate effectively, in non-technical terms, with project team members and clients Experience in managing projects and leading/coaching a project team Keen interest in medical research 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 ❯

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 ❯

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 ❯

don't tick all the boxes, you'll certainly learn on the job! Essential MSc or PhD, or equivalent experience in a quantitative field Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in … version control (e.g. Git), code reviews, CI/CD pipelines, unit testing, and collaborative workflows such as Agile. Experience with optimisation techniques (e.g. gradient descent, Bayesian methods, Lagrangian methods etc) and their practical application Experience in UK General Insurance (Motor and/or Home), with a solid understanding of pricing principles and regulatory governance. Familiarity More ❯