5 of 5 Bayesian Methods Jobs in London

learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesian modelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some ...

Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading data science teams and managing project timelines Excellent communication and stakeholder engagement ...

behavioural, transactional, and demographic data Design and build predictive models to enhance personalized customer experiences across all channels Collaborate on design of test & learn methods to measure CRM initiatives' effectiveness Monitor and optimize model performance through continuous improvement cycles Technical Implementation Transform analytical solutions into production-ready code Implement … metrics Skills ? Relevant experience in Customer Marketing Data Science including applied statistics and machine learning techniques (supervised and unsupervised learning, natural language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ? Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch ...

environment. The role involves applying modelling, optimisation, and simulation techniques to improve operational efficiency and deliver production-ready solutions. Key Responsibilities Apply exploration-exploitation methods and optimisation techniques (surrogate models, Bayesian optimisation, imitation learning). Build dynamic feedback control models and stochastic simulation models. Develop and ...

environment. The role involves applying modelling, optimisation, and simulation techniques to improve operational efficiency and deliver production-ready solutions. Key Responsibilities Apply exploration-exploitation methods and optimisation techniques (surrogate models, Bayesian optimisation, imitation learning). Build dynamic feedback control models and stochastic simulation models. Develop and ...