1 to 25 of 29 Bayesian Methods Jobs

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 ...

other digital businesses.Experience with Snowflake, Power BI, Tableau or similar analytics tools.Exposure to attribution modelling, marketing mix modelling (MMM), Bayesian methods, or advanced experimentation frameworks.Work ShiftHybrid: Western Union values in-person collaboration, problem solving, and ideation whenever possible. We believe this fosters common ways of working ...

intellectually curious, analytical, and passionate about understanding cause-and-effect relationships in complex systems. You bring strong quantitative skills and enjoy applying rigorous methods to high-impact business challenges.Experience applying causal inference techniques in a commercial, product, marketing, or research environment.Strong understanding of causal inference methods. Exposure to experimental … such as Double Machine Learning, Causal Forests, Meta-Learners, and Uplift Models.Experience evaluating incrementality, or uplift using experimental data.Knowledge of Bayesian methods for causal analysis and decision-making.Experience in gaming, e-commerce, or subscription-based products.Experience working with large-scale data using PySpark or equivalent distributed ...

highly desirable.Strong knowledge of underlying mathematical foundations of statistics, exploratory analysis, pricing optimization and analytics (prescriptive and predictive), testing and modelling. Experience in Bayesian modelling is highly desirable.Proficiency in tools such as Google sheets (or Excel), SQL, Python and Tableau.Exceptional attention to detail and proactive mindset with ...

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 ...

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 ...

Stats Background • Outstanding background in probability and statistics • Experience and interest in modern machine learning techniques, for example, deep learning, Bayesian methods and graphical models • Programming experience with python, julia or R You will be joining a progressive and exciting company committed to excellence. They offer ...

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 ...

international clients, from data strategy and collection to modelling, insights, and activation.· Apply econometrics, regression, Bayesian statistics, and machine learning methods to analyse marketing and customer data· Collaborate closely with Managers to understand the project scope, structure, analytical approaches, manage operations and ensure timely delivery.· Build … similar tools.· Experience with Databricks, Azure, or other cloud/data platforms is a plus.· Solid understanding of econometrics, regression analysis, Bayesian statistics, or other advanced modelling techniques.· Experience translating data and model outputs into actionable business recommendations.· Comfortable handling large datasets, optimizing data pipelines, and delivering ...

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 ...

statistics, mathematics, computer science, or equivalent experience with experience in researchProven experience applying machine learning techniques to solve business problemsProven experience in translating technical methods to non-technical stakeholdersStrong 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 visionAbility to write production code and object-oriented programmingWHO ...

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 ...

complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership. The Team This is a unique opportunity to work alongside experts in applied … developing and evaluating AI systems in a regulated industry , with a strong understanding of compliance and privacy standards. Breadth across AI and data science methods -including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand. Proficiency in SQL and ...

complex, high-value problems across the enterprise. You'll architect and deliver generative AI, agentic AI, and LLM-based systems by applying rigorous scientific methods, writing high-quality production code, and communicating results to senior leadership. The Team This is a unique opportunity to work alongside experts in applied … developing and evaluating AI systems in a regulated industry , with a strong understanding of compliance and privacy standards. Breadth across AI and data science methods -including classical ML, causal inference, optimization, and Bayesian approaches-with comfort moving across techniques as problems demand. Proficiency in SQL and ...

with agentic AI frameworks and tooling, such as Bedrock AgentCore, AWS Strands, Azure, and MCP/A2A protocols. Breadth across AI and data science methods, including classical ML, causal inference, optimization, and Bayesian approaches, with comfort working across techniques as problems demand. Proficiency in SQL and ...

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 of performance and critical … tactical 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 with cross ...

Build production-grade Python packages. Follow and build project scaffolds (PowerShell), follow coding standards, and reproducible workflows. Transform analyses into standardized currently best-known methods (cBKM) Process data and automate data flows; manage and optimize data structure & data bases for big data sets. Interact with product and service teams … Bachelor or Master Degree: Statistics/Computer Science/Data Science//Industrial Engineering Expert knowledge of Python, statistical modelling (frequentist and Bayesian) and data visualization Intermediate knowledge of PowerShell, R and SQL AI expert knowledge Project management Comfortable with non-recurrent, high-complexity engineering analyses ...

/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 ...

early clinical development to regulatory approval and lifecycle work. You will provide expert statistical consultation on trial design and analysis, develop and apply advanced methods, and translate complex quantitative concepts into clear insights for cross-functional partners. You will also contribute to scientific communications and external collaboration through publications … doProvide statistical consultation on clinical trial design and analysis across multiple development stages and therapy areas.Develop and implement innovative statistical approaches, including model-based methods using frequentist and Bayesian techniques.Run or guide advanced analyses and simulations to inform design options, sample size, and power trade-offs.Communicate ...