21 of 21 Bayesian Methods Jobs

solutions for complex engineering and optimisation problems. This is an opportunity to join a highly research-driven ML lab, working on probabilistic modelling, Bayesian optimisation and decision-making methods, with a strong emphasis on theoretical rigour and real-world impact. The team regularly publishes … and contributes to open-source ML libraries. The Role You'll conduct original research in areas such as probabilistic models, active learning and Bayesian optimisation, while collaborating closely with other researchers and applied teams. The role blends academic-quality research with practical application, including contributions to product ...

downstream decision making Develop models using classical machine learning techniques such as regression, classification, time series modeling, hierarchical forecasting, and Bayesian methods Incorporate external signals, business context, and domain knowledge into modeling approaches rather than relying solely on historical patterns Partner with data engineering and platform … cases Strong foundation in probability, statistics, and applied mathematics, with demonstrated ability to reason about uncertainty and bias Expertise in classical machine learning methods, including regression, classification, and time series techniques Practical experience deploying models to production, including working with imperfect data, system constraints, and operational requirements Proficiency ...

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 ...

statisticsA 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 ...

statisticsA 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 ...

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 ...

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 ...

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 ...

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 ...

and analytics, and driving significant impact for Sojern’s marketing platform. The team uses state-of-the-art causal inference techniques and advanced scientific methods to continuously enhance the performance, delivery and efficiency of Sojern’s AI-powered marketing products.Position summaryWe are seeking a Senior Data Scientist … pivot functions and complex formulas. 2+ years of experience as a data scientist, ideally within the advertising technology ecosystem.Strong understanding of statistical concepts, measurement methods, and causal inference techniques (e.g. randomized control trials, difference-in-differences, synthetic control modeling, time-series forecasting, hierarchical Bayesian, linear/ ...

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 ...

programming ( C# or Python ) and (b) databases ( SQL and NoSQL ). Experience with various modelling techniques (e.g. Probability Distributions, GLMs, Monte Carlo Simulations, Bayesian Inference, Time-Series Analysis etc.) A demonstrable interest in developing forecasting models for sports. A good understanding of betting concepts and markets. Desirable ...

business stakeholders to ensure top‐quality outcomes to meet internal objectives.Investigate and adopt innovative concepts that offer tangible benefits.Employ techniques like Deep Learning, Bayesian Modelling, Large Language Models, Product Embedding, Recommendation Systems, and Computer Vision.To Be Successful in the Role, You'll Need5+ years of hands ...

related field Strong Python and C++ skills Experience with frameworks such as PyTorch, TensorFlow or JAX Background in probabilistic modelling, Bayesian methods or reinforcement learning Desirable: Experience working with robotic systems or autonomous platforms Familiarity with SLAM, path planning or multi-agent systems Knowledge ...

related field Strong Python and C++ skills Experience with frameworks such as PyTorch, TensorFlow or JAX Background in probabilistic modelling, Bayesian methods or reinforcement learning Desirable: Experience working with robotic systems or autonomous platforms Familiarity with SLAM, path planning or multi-agent systems Knowledge ...

from framing the question to delivering outcomes.Ability to communicate clearly in writing and speech, adapting technical detail to suit different audiences.BonusUnderstanding of Bayesian statistics, including experience or interest in applying hierarchical Bayesian models.Experience building machine learning models from scratch, including creating custom optimisers.Knowledge ...

Automation, Scripting & Visualization: Leveraging automated data processing, scripting, and interactive visualization to uncover insights, streamline workflows, and support sustainability goals. Design of Experiments & Bayesian Optimization: Implementing Bayesian and state-of-the-art approaches to maximize experiment efficiency and accelerate material and process development. Materials ...

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 ...

modelling software to enhance cyber and business resiliency efforts. Collaborating closely with a quantitative data scientist, you will spearhead the creation of a Bayesian inference-based modelling platform aimed at forecasting the risk and business consequences of potential disruptive events. This pivotal role plays a crucial part … teams, risk analysts, data scientists and resiliency stakeholders to define model inputs, risk scenarios, and system architecture requirementsTranslate mathematical and statistical models (e.g. Bayesian networks, probabilistic graphical models) into performant software modules.Develop data ingestion and transformation pipelines to source data from internal systems and threat intelligence sourcesLead ...

OverviewData Scientist role at Singular Recruitment in London, England, United Kingdom. This position offers a unique opportunity to combine technical challenges with creativity in a collaborative, high-standard work environment. You’ll have the chance ...

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 ...