12 of 12 Bayesian Methods Jobs in the UK excluding London

tools (Pandas, NumPy, Polars, scikit-learn, etc.) Experience building ML models end-to-end: feature engineering, training, evaluation, and deployment Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools Excellent communication skills … multimodal data Experience working with big data ecosystems (Spark, Ray, Snowflake, BigQuery, etc.) Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming Why Join Gain exposure to cutting-edge AI research workflows, collaborating closely with data scientists, ML engineers, and research leaders shaping ...

tools (Pandas, NumPy, Polars, scikit-learn, etc.) Experience building ML models end-to-end: feature engineering, training, evaluation, and deployment Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools Excellent communication skills … multimodal data Experience working with big data ecosystems (Spark, Ray, Snowflake, BigQuery, etc.) Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming Why Join Gain exposure to cutting-edge AI research workflows, collaborating closely with data scientists, ML engineers, and research leaders shaping ...

tools (Pandas, NumPy, Polars, scikit-learn, etc.) Experience building ML models end-to-end: feature engineering, training, evaluation, and deployment Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools Excellent communication skills … multimodal data Experience working with big data ecosystems (Spark, Ray, Snowflake, BigQuery, etc.) Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming Why Join Gain exposure to cutting-edge AI research workflows, collaborating closely with data scientists, ML engineers, and research leaders shaping ...

tools (Pandas, NumPy, Polars, scikit-learn, etc.) Experience building ML models end-to-end: feature engineering, training, evaluation, and deployment Solid understanding of statistical methods, experiment design, and causal or quasi-experimental analysis Familiarity with modern data stacks: SQL, distributed datasets, dashboards, and experiment tracking tools Excellent communication skills … multimodal data Experience working with big data ecosystems (Spark, Ray, Snowflake, BigQuery, etc.) Familiarity with statistical modeling frameworks such as Bayesian methods or probabilistic programming Why Join Gain exposure to cutting-edge AI research workflows, collaborating closely with data scientists, ML engineers, and research leaders shaping ...

command of diverse methodologies, with a solid grasp of data science and statistical techniques (e.g., supervised/unsupervised machine learning, model cross-validation, Bayesian inference, time-series analysis). Strong Python programming skills and an excellent proficiency of the basic libraries for data science (e.g., NumPy, Pandas ...

testing). Ideally, you have proven experience developing and deploying Marketing Mix Models in a commercial environment. Strong statistical foundation, ideally including Bayesian methods. A passion for building production-quality, source-controlled data products, with data engineering skills to help the team own more of its data ...

data, or optimisation Collaborative communicator, organised, proactive, and curious Desired Skills Masters degree in ML, mathematics, or statistics Knowledge of probabilistic and Bayesian modelling Solid software-engineering principles and experience with an OO language Familiarity with cloud platforms (Azure, AWS, or GCP) and IaC tools such ...

development. • Collaborate with engineering to deploy models in high-performance, production environments. • Publish internal technical notes or contribute to external research when appropriate. • Explore methods in synthetic data generation, foundation-model adaptation, and model compression. Your Profile • Ideally holding a Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Mathematics … advanced AI research. • Proficient in Python; experience with PyTorch or JAX. • Understanding of reinforcement learning, multi-agent systems, probabilistic/Bayesian methods, or large-scale training. • Curiosity-driven mindset, strong problem solving, and the ability to work cross-functionally. • English is the working language; additional languages ...

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 ...

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 ...

Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's reinventing … training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to push ...