1 to 25 of 45 Bayesian Methods Jobs in London

business questions into analytical problems and build solutions using visualization techniques, dashboards, machine and deep learning, and statistical modelling. Search and develop new algorithms, methods, statistical models and business models, providing insight into structured and unstructured data. Apply R-based analytical and statistical techniques to solve business problemsApplying data … biostatistics, or other quantitative field (or equivalent).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 ...

business questions into analytical problems and build solutions using visualization techniques, dashboards, machine and deep learning, and statistical modelling. Search and develop new algorithms, methods, statistical models and business models, providing insight into structured and unstructured data. Apply R-based analytical and statistical techniques to solve business problems Applying … other quantitative field (or equivalent). 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 ...

Economics, Engineering etc.)Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra. Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks, machine learning, clustering, or similar methodologies. Proficiency ...

analysis Have in depth understanding of statistical modelling/ML techniques for time series forecasting (ARIMA, ETS, Prophet, Time Series pattern detection, and ML methods) Strong experience with Causal inference, Intervention analysis, Counterfactuals Estimation, Optimization and Scenarios simulation Solid experience with Probabilistic Programming and Bayesian Methods ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering … analytics, or a related domain Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop Exposure to Bayesian methods, causal inference, or multi-armed bandit approaches Experience collaborating with Machine Learning Data Science teams to validate and scale models for business impact Familiarity ...

build datasets suited for modelling and in-depth analysis. Design and execute measurement frameworks — including A/B testing, causal impact analysis, and multivariate methods — selecting the appropriate technique based on the business question and clearly communicating trade-offs. Build, evaluate, and iterate on statistical models (e.g. regression, clustering … analytics, or a related domain Familiarity with big data querying tools such as Presto, Hive, BigQuery, or Hadoop Exposure to Bayesian methods, causal inference, or multi-armed bandit approaches Experience collaborating with Machine Learning Data Science teams to validate and scale models for business impact Familiarity ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Skilled in handling large datasets, optimising pipelines, and delivering high-quality outputs Track record of translating complex model results ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus.· Strong understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques.· Skilled in handling large datasets, optimising pipelines, and delivering high-quality outputs· Track record of translating complex model results ...

least 3 data or ML products from problem definition to production deployment and monitoring. Demonstrated proficiency in clustering, predictive modeling, reinforcement learning, and Bayesian statistics. Hands‐on experience in software engineering, MLOps, and deploying machine learning models at scale. Proficiency in SQL, Python, and familiarity with ...

deep learning, neural networks, reinforcement learning, and transfer learning. Familiarity with traditional machine learning algorithms such as random forests, SVM, logistic regression, and Bayesian modelling for model building, validation, and testing. Familiarity with cloud platforms (e.g., Bedrock, AWS, Azure) for model deployment and the creation of production ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs. Track record of translating complex model ...

Excel, and visualisation tools; experience with Databricks, Azure, or other cloud/data platforms is a plus. Deep understanding of econometrics, regression, Bayesian statistics, and advanced modelling techniques. Proven ability to handle large datasets, optimise pipelines, and deliver high-quality outputs. Track record of translating complex model ...

and non-technical stakeholders. Collaborative mindset and ability to work across data science, engineering, and business teams. Desirable Ability to build and evaluate Bayesian models using PyMC or Stan, with a focus on real-world forecasting applications. Formal work experience not required. Experience in pricing analytics, demand ...

experimental data, and in your penultimate year of study. Experience working with datasets using Python, R, SAS, MATLAB, or other statistical software. Experience with methods of statistical data analysis (e.g., linear models, hypothesis testing, multi-level models, Bayesian methods, etc.). Preferred qualifications: Experience with … search techniques. Produce quantitative and qualitative modeling of business dynamics, user behavior, and more. Identify areas for further investigation as well as creating innovative methods of analysis. Please complete your application before 23rd October 2026. We encourage you to apply as early as possible as we review applications ...

Track record of promoting statistical rigour and experimental best practices in your prior roles. Prior experience using causal inference/econometric techniques and bayesian methodologies for hypothesis testing. Prior experience using large datasets with distributed computing (e.g. spark, hadoop or other map-reduce tech)Experience working ...

through to multinationals, helping them secure highly sought after skill sets. Key words: Data Scientist, Algorithm Developer, Equity Research, Investments, Quantitative Research, Bayesian Statistics, Mathematics, Computer Science, Analytical Algorithms, Python. C++, Monte Carlo. ...

international clients, from data strategy and collection to modelling, insights, and activation.· Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data· Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery.· Build … similar tools.· Experience with Databricks, Azure, or other cloud/data platforms is a plus.· Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques.· Experience translating data and model outputs into actionable business recommendations.· Comfortable handling large datasets, optimizing data pipelines, and delivering ...

products PhD or other experience in a research environment Deep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering Strong stats or math background At Fin, we want to give people what they need to do the best work ...

similar. ● PhD in Statistics or another area involving lots of work with messy data (e.g., Physics, Computational Biology). ● Extensive background in Bayesian inference, state-space models, filtering algorithms, etc. ● Excellent programming skills and experience implementing efficient algorithms for high-dimensional problems. Any prior exposure to sports ...

Engineering degree. Outstanding background in probability and statisticsExperience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical modelsProgramming experience with python, julia or RYou will be joining a progressive and exciting company committed to excellence. They offer an excellent working ...

data pipelines using dbt, Airflow, and Snowflake. Beyond querying, you use Python for advanced automation and forecasting, and you apply statistical rigor (e.g., Bayesian statistics, causal inference) to solve complex product problems. Commercial & Risk Mindset: You possess deep commercial fluency, understanding the unit economics of a fintech ...

into a compelling product vision and strategic roadmap. Deep expertise in advanced measurement techniques including Marketing Mix Modeling (MMM) (including various methodologies like Bayesian), Multi-Touch Attribution (MTA), Incrementality testing, and marketing experimentation. Strong understanding of marketing data sources, data ingestion, transformation, and reporting challenges. Deep expertise ...

algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g., target encoding). Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production‐grade Python code for both model training and inference. Excited to leverage LLMs ...

supervised ML algorithms, tuning, and performance evaluation. Experience with a range of feature engineering techniques (e.g. target encoding).Solid grasp of frequentist and Bayesian statistics for parameter estimation and experimentation. Experience in writing clean, production-grade Python code for both model training and inference. Excited to leverage ...

Tools: C++, Python, Git, Docker, CI/CD, Linux, Docker/Podman ML specific skills Stochastic processes: behavior trees, FSMs, MDPs Learning: RL, Bayesian networks (and BBP) Scripting languages: PDDL, RDDL Nice to Haves Experience with SLAM, computer vision applied to UAVs Knowledge of AI safety principles ...