1 to 25 of 100 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 ...

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 ...

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 ...

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 … pricing, marketplace analytics, or a related domainFamiliarity with big data querying tools such as Presto, Hive, BigQuery, or HadoopExposure to Bayesian methods, causal inference, or multi-armed bandit approachesExperience collaborating with Machine Learning Data Science teams to validate and scale models for business impactFamiliarity with inclusive ...

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 ...

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 ...

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 ...

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 ...

communication skills. Beneficial to have: Experience in a similar role in a professional football environment. Experience with Time-Series Analysis & Forecasting. Experience with Bayesian inference/MCMC. What's in it for you? We are committed to ensuring everyone can flourish in their roles. To achieve this ...

fundamentals Advanced data skills: statistical modelling, machine learning, time‐series forecasting, demand prediction, optimisation, inventory management Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plus Preferred Experience Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e‐commerce, or similar dynamic ...

fundamentals Advanced data skills: statistical modelling, machine learning, time-series forecasting, demand prediction, optimisation, inventory management Experience with dynamic pricing, stochastic processes, or Bayesian inference is a plus Preferred Experience Background in pricing, forecasting or optimisation roles within airlines, hospitality, car rentals, e-commerce, or similar dynamic ...

and machine learning. Statistics & Math: Deep understanding of statistical inference, regression analysis, probability theory, decision trees, and hypothesis testing (p-values, confidence intervals, Bayesian testing etc.). Data Visualization: Hands‐on experience building interactive dashboards using tools like Power BI, Looker, or Python libraries. Experience: 3+ years ...

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 deploy production‐grade ML systems with scalability and robustness in mind. Translate state‐of‐the‐art research (probabilistic modelling, Bayesian methods, optimisation) into customer‐ready solutions. Work collaboratively within a cross‐functional team to deliver measurable impact to global shipping customers. Communicate complex ideas clearly … What We’re Looking For Familiarity and some experience with machine learning research or applied ML, ideally with expertise in probabilistic models and Bayesian statistics. Experience bringing ML models from prototype to production with supervision. Strong analytical and problem‐solving abilities, and confidence working across disciplines following ...

role has a particularly interesting data and analytical dimension. You'll be working alongside concepts including: Machine Learning Data Science Bayesian Methods Gaussian Processes Probability Statistics You don't need to be a Data Scientist, but experience in these areas would give you an excellent opportunity … Software Engineering, Mathematics, Engineering or a related discipline. The ability to work independently while collaborating with multidisciplinary teams. Ideally, exposure to ML, statistics, Bayesian modelling or probabilistic methods. This is a role for someone who wants technical depth, variety and ownership. You'll be solving genuinely complex ...

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. ...

what questions should be explored next. Key Responsibilities & Skills ** Develop predictive models and forecasts to identify potential future outcomes and emerging trends ** Applying Bayesian modelling, uncertainty estimation and statistical validation ** Carry out segmentation and subgroup analysis to identify meaningful differences and patterns ** Analyse longitudinal and time-series ...

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/ ...