1 to 25 of 65 Bayesian Methods Jobs

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 ...

and MMM frameworks such as Google Meridian, Meta Robyn, or LightweightMMM. Causal inference, experiment design, geo-experiments, or incrementality testing; comfort with both Bayesian and frequentist approaches. Cloud and analytics platforms (Azure, AWS, GCP, Databricks, Microsoft Fabric, Snowflake) and exposure to MLflow, MLOps, or Spark/PySpark. ...

related to consumer behaviour, market trends, and campaign performance. - Build, maintain, and apply statistical and predictive models, including regression, econometrics, Bayesian methods, and Marketing Mix Modelling (MMM). -Develop dashboards, charts, and- visualizations to communicate insights effectively to clients and internal teams. - Assist in developing marketing ...

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 ...

cases as well as models. Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system ...

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 ...

cases as well as models. Train Machine Learning Models: Use machine learning and statistical modelling techniques such as recommendations, reinforcement learning, decision trees, Bayesian analysis, neural networks and transformers to develop and evaluate algorithms to address business use cases and/or to improve product/system ...

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 ...

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 ...

pricing models. Turning pricing opportunities into measurable hypotheses, experiments and production changes. Evaluating pricing performance through backtesting, online testing and commercial metrics. Developing Bayesian, multi-armed bandit and other optimisation approaches for dynamic pricing. Working with commercial, finance and product teams to understand pricing performance and recommend … code, testing and code review, alongside strong SQL. A solid grounding in machine learning techniques such as gradient boosting, GLMs, Bayesian methods and multi-armed bandits, or comparable experimentation and optimisation methods. Experience designing, running and evaluating pricing experiments using both commercial and statistical measures. ...

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. ...

required to obtain UK Security Clearance. Desirable Experience Experience with any of the following would be beneficial: Statistical modelling, Bayesian methods, uncertainty estimation, or probabilistic techniques. Synthetic data generation, multi-modal AI, or action recognition. Machine learning development tools, experiment tracking, dataset management, or CI/ ...

technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real‐world loops. Familiarity with retrosynthesis ML, computer‐aided synthesis planning (CASP), or reaction‐condition/ ...

Analyst or Data Scientist Minimum 2:1 in a Quantitative subject ideally Masters Experience OR an interest in Modelling – CHAID, Cluster Analysis, Bayesian Algorithms, NN, Experience with visualisation tools would be nice Python and SQL experience ideally - Python a MUST Experience in a Data Science role with ...

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 ...

shipping ML productsPhD or other experience in a research environmentDeep experience in an applicable ML area - E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clusteringStrong stats or math backgroundVisualization, data skills, SQL, matplotlib, etc. At Fin, we want to give people what they need ...

Scrum Nice to Have : Experience with UI/UX design principles. Experience deploying cloud infrastructure as code (e.g. AWS). An understanding of Bayesian statistics. Experience with accessibility, inclusive design or motion design. Location: This role is on-site at either our Exeter or Bristol office. ...