1 to 25 of 38 Bayesian Methods Jobs

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. ...

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 big data technologies (e.g. ...

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 ...

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. 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 ...

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 ...

Python, SQL, 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 outputs ...

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 ...

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 ...

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 ...

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/ ...

production.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 in a fast ...

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. ...

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/ ...

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 ...

explain complex technical concepts clearly Strong programming skills in Python, with experience in C++ for production or performance-critical systems Desirable: Experience with Bayesian inference, uncertainty estimation, probabilistic modelling, or state estimation Familiarity with custom loss functions, action recognition, synthetic data, or multi-modal neural networks ...

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 Benefits Competitive salary and equity in a fast‐growing start‐up We serve lunch every weekday ...

rich environments Strong statistical knowledge Experience with product analytics and behavioural tracking Experience mentoring or coaching other analysts Nice to have Knowledge of Bayesian or Frequentist experimentation approaches Experience with event-level analytics platforms Predictive analytics exposure The team You'll report into the Analytics Team Lead ...

teams to design and implement new statistical and machine learning features across Optimizely’s product suite. Conduct rigorous testing and validation of new statistical methods and ensure seamless integration into the platform. Analyze product performance data to optimize existing features and provide actionable recommendations for improvement. Leverage AI agents … deploy new statistical capabilities. Research and Innovation Partner with academic and industry researchers to explore cutting-edge statistical methods and machine learning innovations. Identify emerging trends in experimentation and statistics that could enhance Optimizely’s offerings. Propose and prototype advanced statistical techniques to solve challenging business problems faced ...

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 ...

work with product and engineering priorities. Nice to have Experience quantifying uncertainty in large models — calibration and confidence estimation via Bayesian methods, ensembling, steering, or prompt-based approaches. Experience with machine translation, multilingual NLP, or document-/layout-aware modelling experience. Familiarity with MoE-specific training ...

duties and responsibilities will include, but won’t be limited to building and improving sports prediction modelsTo research recent advances in Bayesian updating to better extract signals from noisy dataTo design and build your own models using your own ideasTo work closely with expert traders and developers ...