1 to 25 of 61 Bayesian Methods Jobs in London

Understand complex and critical business problems, formulates integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. To manage the implementation and adherence to the … or equivalent). More than 3 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods More ❯

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. … or equivalent). More than 6 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods More ❯

Understands complex and critical business problems from a variety of stakeholders and business functions, formulate integrated analytical approach to mine data sources, employ statistical methods and machine learning algorithms to contribute solving unmet medical needs, discover actionable insights and automate process for reducing effort and time for repeated use. … or equivalent). More than 6 years experience in clinical drug development with extensive exposure to clinical trials. Strong knowledge and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods More ❯

Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices Work towards long-term research goals, while identifying intermediate milestones Build relationships and collaborate with academics and institutions Explore new … research experience, or 5 or greater years of work experience (actual job title/position will be commensurate to experience) Good background in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with Deep Learning … abilities in Python and/or C++ Preferred Qualifications: 2D & 3D Generative AI Reinforcement Learning LLMs and Natural Language Processing Computational geometry and geometric methods (e.g. shape analysis, topology, differential geometry , discrete geometry , functional mapping, geometric deep learning, graph neural networks) Multi-modal deep learning and/or information More ❯

Python skills; familiarity with R for MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with More ❯

Python skills; familiarity with R for MMM. Expertise in regression modeling, statistical and ML techniques . Experience with probabilistic programming, Bayesian methods, and MCMC. Proficient in SQL and/or Spark for large-scale data mining. Solid understanding of statistical foundations and mathematical modelling. Familiarity with More ❯

Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a … background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow More ❯

ll work on a broad spectrum of problems ranging from marketing measurement to algorithmic optimization. Our solutions combine advanced ML, causal inference, and Bayesian modeling to drive marketing effectiveness at scale. The Challenge: While you'll initially focus on building YouTube as Amazon's next variable marketing … audience targeting and content optimization Customer behavior modeling frameworks Why You'll Love It: Work on diverse problems spanning ML, causal inference, and Bayesian statistics Tackle challenges across multiple scientific domain and use cases Develop novel approaches for ML & science, specially within marketing Build solutions that directly … markets If you're excited about advancing the state of the art in marketing science through innovative applications of ML, causal inference, and Bayesian statistics, while working on diverse problems that directly impact millions of customers, we want to hear from you. BASIC QUALIFICATIONS PhD, or a More ❯

practical solutions for predictive analytics. Experience in solution design, architecting and outlining data analytics pipelines and flows. Advanced Mathematics skills including experience with Bayesian statistics, linear algebra and MVT calculus, advanced data modelling and algorithm design experience. Design and deployment experience using Tensor Flow, Spark ML, CNTK More ❯

reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3. Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation). Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL). Exposure to spatiotemporal data More ❯

reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3. Practical knowledge of optimization algorithms and probabilistic modeling techniques (e.g., Bayesian methods, Gaussian Belief Propagation). Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL). Exposure to spatiotemporal data More ❯

tools such as Google Looker and working with Google's BigQuery. Experience in design and evaluation of A/B tests. Familiarity with Bayesian statistics, especially for hypothesis testing. Experience with application of optimization theory or reinforcement learning based on automated A/B testing. Projects you More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we're open-minded, so definitely include More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we're open-minded, so definitely include More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we’re open-minded, so definitely include More ❯

Bonus: Experience implementing solutions in a production environment (e.g., continuous integration). Experience with Python. (Note: we mostly work in Python.) Experience with Bayesian statistics. The salary We expect to pay from £70,000 - £90,000 for this role. But, we’re open-minded, so definitely include More ❯

Job Description Summary - Understands complex and critical business problems from various stakeholders and functions, formulates integrated analytical approaches to mine data sources, employs statistical methods and machine learning algorithms to solve unmet medical needs, discover actionable insights, and automate processes to reduce effort and time for repeated tasks. - Manages … related quantitative field (or equivalent). Over 6 years of experience in clinical drug development with extensive clinical trial exposure. Strong knowledge of statistical methods like time-to-event analysis, machine learning, meta-analysis, mixed-effect modeling, Bayesian methods, variable selection techniques (e.g., lasso, elastic More ❯

field Advanced programming skills in R or Python, C# or Java, and SQL Experience with modeling techniques (e.g., Probability Distributions, GLMs, Monte Carlo, Bayesian Inference, Time-Series) Interest in developing sports forecasting models Nice to Haves… PhD in a quantitative field Experience with supervised/unsupervised/ More ❯

Must have led multiple projects on MMM analytics Experience in pricing and promotion analytics is a plus Must have experience with Databricks Implemented Bayesian regression on python. Exposure to libraries like numpy, pandas, sklearn, pymc3 Hands on experience in PowerPoint/Excel is a must Strong logical More ❯

enable companies in the entertainment industry to significantly increase profit margins. You’ll use a raft of different techniques from timeseries analysis to bayesian statistics, reinforcement learning & Monte Carlo Simulations. Your Experience : You’ll likely come from a strong quantitative degree background in Science or Maths and More ❯

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 to More ❯

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 to More ❯

flexibility to learn by iteration. Desirable Attributes Masters/PhD in STEM subject. Understanding of functional and object-oriented programming paradigms. Experience with Bayesian models, Markov chains and multivariate time-series modelling. Experience with widely used probabilistic programming and machine learning libraries such as Stan, PyMC3, Scikit More ❯

Ability to explain ideas and present results to non-technical audiences. Strong stakeholder management skills. Experience with marketing mix models and/or Bayesian time series would be a big plus. Strong theoretical understanding and experience with key classification and regression models is a plus. By joining More ❯

Ability to explain ideas and present results to non-technical audiences. Strong stakeholder management skills. Experience with marketing mix models and/or Bayesian time series would be a big plus. Strong theoretical understanding and experience with key classification and regression models is a plus. By joining More ❯