1 to 25 of 29 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. ...

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. 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 ...

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 ...

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 ...

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/ ...

with time‐series modelling and industrial or IoT data. You have experience in any of: dynamical systems, reinforcement learning, system identification, optimisation or Bayesian statistics. You are used to working in a fast‐paced startup environment with an agile process. You have a degree in machine learning ...

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 ...

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 ...

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 ...

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 ...

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.Benefits We are a well treated bunch, with awesome benefits! If there ...

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 ...

computer science, or equivalent experience with experience in research Proven experience applying machine learning techniques to solve business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in Python and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/…/keras, langchain). R and C++ optional. Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate models, transformers, Knowledge Graphs, Agents, Graph NNs, Deep Learning, computer vision Ability to write production code and object-oriented ...

platform. You will be joining a highly talented team of scientists and engineers who are tackling a difficult technical challenge and applying new computational methods to real-world problems. The role offers autonomy, access to leadership, and the opportunity to help shape both technology strategy and future product direction. … simulation, or predictive analytics. Excellent Python programming skills and experience working with modern scientific computing frameworks. Any additional experience with digital twin technologies, Bayesian modelling, or working knowledge gained within an engineering or life sciences setting would be highly advantageous. What's on Offer Opportunity to play ...

and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership … global scale. Responsibilities Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science. Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors ...

and strategic level. Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling . Understanding of Bayesian approaches and modeling frameworks. Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership … functional stakeholders. Responsibilities: Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science. Partner with internal teams in advanced analytics work including experimentation, measurement and modeling. Identify patterns and behaviors that are effective predictors ...

/equating and research studies, supports the completion of studies by others, and develops white papers and research summaries. Implements and improves psychometric research methods and processes at MetaMetrics according to best practices, industry standards, and academic literature. Maintains awareness of psychometric literature and methods regarding test and … delivery methods (e.g., fixed-form, computer adaptive, and linear-on-the-fly), statistical methods (e.g., simulation studies), and computational psychometrics (e.g., machine learning, Bayesian inference). Provides ad hoc or planned expert consultation to clients and their stakeholders (e.g., technical advisory committees) regarding methods ...

efficient data transformations using distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems.Mentor junior team members and utilise model explainability methods to drive feature performance improvements.About You5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.Deep … understanding of frequentist and Bayesian statistics, plus supervised and unsupervised modelling techniques.Proven experience modelling complex interactions (e.g., cluster or network effects).Expertise in model explainability to tune feature engineering and understand feature interactions.Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical ...