13 of 13 Remote/Hybrid Bayesian Methods Jobs in the UK

with our AIOps engineering teams to productionize and scale analytical capabilities beyond traditional manual analysis. By leveraging your deep understanding of marketing data, statistical methods, and emerging AI technologies, you'll enable data-driven marketing strategies that maximize ROI and competitive advantage. Develop and maintain econometric models to measure … budget allocation Hands-on experience working with Google Analytics data and other marketing platforms Experience with marketing mix modelling, incrementality testing, and causal inference methods Familiarity with marketing data sources and platforms (Facebook Ads, programmatic platforms, etc.) Strong knowledge of experimental design and statistical modelling techniques including regression analysis ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

detection", etc Analyse data to help in better decision making Supporting initiatives for data integrity and normalization Data mining using state‐of‐the‐art methods Doing ad‐hoc analysis and presenting results in a clear manner Managing and designing the reporting environment, including data sources, security, and metadata Qualifications … Machine learning development projects Job Skills & Responsibilities: Experience in machine learning Exposure to machine learning models and corresponding statistics like K‐means, Bayesian, Clustering Strong technical skills with Python along with NumPy, Pandas, Scikit‐Learn Machine learning experience -> predictive and prescriptive modelling Data wrangling and data cleansing ...

Looking For Experience with Marketing Mix Modelling or statistical modelling Strong Python skills and experience working with large datasets Understanding of Bayesian statistics and attribution methodologies Experience with tools such as Meridian, Robyn, PyMC, or similar Ability to communicate technical findings clearly to stakeholders Strong attention ...

grow and you to mentor. What you bring to the table Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Ability to scope and effectively deliver projects. Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend … applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: operator learning (neural operators), or other probabilistic methods for PDEs; geometric deep learning or other 3D computer vision methods for point‐cloud or mesh‐structured data; generative models for geometry and ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

experiments, RCTs), and Multi-Touch Attribution. Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, PyMC-Marketing, LightweightMMM, Bayesian regression, or working closely with vendors who do. Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control … mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments. Nice to haves: Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement. Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap ...

bring to the table Ability to scope and effectively deliver projects. Enthusiasm about using machine learning, especially deep learning and/or probabilistic methods, for science and engineering. Strong problem‐solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly. Excellent collaboration and communication skills … applied statistics, mathematics, physics, engineering, or a related field, with particular expertise in any of the following: operator learning (neural operators), or other probabilistic methods for PDEs; geometric deep learning or other 3D computer vision methods for point‐cloud or mesh‐structured data; generative models for geometry and ...