5 of 5 Bayesian Methods Jobs in Manchester

communicate technical concepts to marketing and commercial stakeholders. Comfortable using AI to improve experiment design, workflow efficiency and analytical processes. Nice to have Bayesian modelling (PyMC, Stan). Value-based bidding. Offline conversion uploads. Marketplace, travel, subscription or considered-purchase environments. LTV and payback modelling experience. ...

rich environments Strong statistical knowledge Experience with product analytics and behavioural tracking Experience mentoring or coaching other analysts Nice to have Knowledge of Bayesian or Frequentist experimentation approaches Experience with event-level analytics platforms Predictive analytics exposure The team You'll report into the Analytics Team Lead ...

team, contributing your statistical and ML expertise across other client workstreams.KEY RESPONSIBILITIESDesign data-driven solutions tailored to client challenges, leveraging advanced analytical methods, ML models, and AI technologies to deliver business value.Lead media effectiveness projects for our clients - designing, building and interpreting Media Mix Models, incrementality studies, and multi … attribution solutions.Solid understanding of marketing strategy, media channels, customer journeys, and how to translate media investments into business impactA strong foundation in traditional statistical methods (e.g. regression, time series, probabilistic models), combined with a proactive mindset for exploring and applying cutting-edge developments in ML and AI.Deep understanding ...

knowledge sharing across the discipline. What we're looking forExperience as a Data Analyst (or similar role) within consumer-facing product teams Experience applying methods for statistical inference (e.g. Bayesian, Frequentist) and analysing A/B tests Experience in planning and completing analytical tasks on time ...

each stage of the consumer’s lifecycle. Experience overseeing experimentation programmes and practices that inform product or business decisions. A good understanding of methods for statistical inference (e.g. Bayesian, Frequentist) and familiarity with predictive analytics techniques is highly beneficial. Working knowledge of common analytics tools used ...