8 of 8 Remote/Hybrid Bayesian Methods Jobs

Modelling Develop, evolve, and enhance data science models across multiple business areas. Lead a team of data scientists across several workstreams using rule-based methods, supervised and unsupervised learning, forecasting, and optimisation techniques. Work closely with product owners, data engineers, and ML engineers to deliver high-quality, scalable … algorithms, statistical modelling, and probabilistic programming. Expert programming ability in Python, R, and SQL, with deep experience in time series modelling. Understanding of forecasting methods: ARIMA, ETS, Prophet, time series pattern detection, and ML-based forecasting. Advanced experience in: Causal inference Intervention analysis Counterfactual estimation Mathematical optimisation Scenario simulation ...

their most pressing strategic challenges. Technical Leadership: Architect robust, scalable data pipelines and state-of-the-art models (including LLMs, Reinforcement Learning, or Bayesian Inference) tailored to specific client needs. Mentorship: Guide and upskill junior Data Scientists, fostering a culture of rigorous peer review, clean coding standards ...

level. Ability to write complex CTEs, window functions, and optimize joins for distributed systems. Experience with Marketing Mix Models (MMM). Understanding of Bayesian inference, Adstock transformations, and saturation curves. Useful experience Hands-on experience with at least one major DCR environment. Deep understanding of hypothesis testing ...

problems (e.g., generating the "perfect" rota). Model Innovation: Experiment with state-of-the-art techniques (e.g., Deep Learning, Transformers, Bayesian methods) to improve accuracy and robustness. Data Strategy: Work with proprietary and public datasets to uncover new features and signals that improve model performance. Production ...

like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. Bayesian Modelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate ...

office on a hybrid working model. Purpose of the role: The Graph, ML Data Scientist will specialise in leveraging graphical models (such as Bayesian networks and Markov models) and probabilistic reasoning techniques to uncover insights from complex data sets using advanced data analysis and predictive modelling. What ...

research project "ICEBAY - Temperature reconstruction combining boreholes thermometry and ice-cores with Bayesian hierarchical modeling." Development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data Collaboration in an international team on related research … Python or C/C++) Interest in modeling and solving a complex, coupled inverse problem in a relevant interdisciplinary application Ideally, experience in Bayesian inference or Bayesian hierarchical modeling Good command of English (working language within the team, international collaboration) A competent, proactive personality ...

partnered with a fast-growing research technology startup using AI to transform how organisations understand people. The business combines advanced analytics with modern research methods to deliver deeper insights, faster and at significantly lower cost than traditional research approaches. As the company launches a new AI-driven product, they … and segmentation Automate repeat analytical tasks for trackers and long-running projects Run end-to-end research projects (primarily quant; some qual/mixed methods) Contribute to proposals and RFPs About You Essential 3+ years' experience in analytics and/or research using survey data Hands-on experience with ...