19 of 19 Bayesian Methods Jobs

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 performance ...

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-ready pipelines.Proficiency ...

exposure to tools such as Meridian, Robyn, or PyMC Proficiency in Python and experience working with cloud platforms such as GCP Understanding of Bayesian statistics and marketing attribution concepts Ability to communicate technical findings clearly to non-technical audiences Interest in applying AI tools to enhance data ...

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 ...

years line management responsibilities.Hands-on experience in population PK/PD, disease progression modeling, and clinical trial simulations.Strong understanding and knowledge of Bayesian methodologies, model-based meta-analyses, PBPK, QSP, and AI/ML in Pharmacometrics.Expertise in R, NONMEM or related pharmacometrics software.Are you ready ...

Stats or 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 ...

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 ...

Make your mark for patientsWe are looking for a Principal Computational Methodologist who is curious, collaborative, and impact-driven to join our Advanced Methods and Data Science team within Biometrics and Data Science, based in any of our Brussels (Belgium), Slough (UK) or Raleigh (US).About the roleYou will … help shape how advanced AI, machine learning, and computational methods support clinical development. You will design, validate, and deploy models that help teams make evidence-based decisions in areas such as biomarker discovery, clinical trial design, operational efficiency, and patient experience. You will guide scientific thinking, turn complex methods ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

continuously learn and improve Desirable: Study design and sample size experience Regulatory experience A basic understanding or willingness to learn Bayesian methods and causal inference modelling Experience within Oncology and/or CNS therapeutic areas Opportunities at Veramed Presenting at conferences and authoring publications Developing and ...

/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 ...

reimbursement agency, or academic institution (pharma affiliate experience is a plus). Demonstrate in-depth knowledge of Access and HTA, clinical research and development methods, and international payer evidence requirements. Skilled in research design and statistical methods, such as Generalized Linear Models, Survival analysis, Network Meta-Analysis, and … Bayesian statistics and are proficient in R and GitLab (experience with SAS, Python, WinBUGS, JAGS, or other relevant statistical software is a plus). Strong strategic, collaboration, and communication skills, strong organization, planning, and prioritization skills with an ability to meet tight deadlines, and strong written and ...

energised by the opportunity to grow.What You’ll DoExperimentationDesign and analyse A/B tests across Viator’s marketplace, applying sound statistical methods to interpret results and support confident decision-makingChampion experimentation best practices: power calculations, guardrail metrics, and multiple testing corrections.Develop your mastery of causal inference and advanced … data science, analytics, or quantitative research role at a data-driven organization; strong product analysts who are actively upskilling in data science methods are encouraged to applyAdvanced SQL skills and hands-on experience querying and manipulating large datasetsProficiency with data visualisation tools (Tableau, Looker or equivalent) Experience with ...

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 ...

promotion of early-career scientists Expertise in an interdisciplinary field of research combining bioprocess engineering, automation, and process optimization Application of modern methods of robotics, such as: Stochastic and data-driven learning approaches Precise monitoring and control using microcontrollers (μC) Novel methods of image processing Research experience … following areas: Machine learning (e.g., deep learning) for process models Optimization of bioprocess development workflows across different scales (e.g., multi-fidelity Bayesian optimization) Teaching responsibilities in the university's bachelor and master programs , including courses such as: Industrial Biotechnology Pharmaceutical Bioprocess Engineering Qualifications Demonstrated initial scientific achievements ...