trends and competitor behaviours to build predictive models that inform pricing strategy. Apply advanced statistical and machine learning techniques, including generalized linear models (GLMs), gradientboosting, and deep learning, to extract insights from large, complex datasets. Work with data engineers to ensure the ingestion, transformation, and deployment of More ❯
trends and competitor behaviours to build predictive models that inform pricing strategy. Apply advanced statistical and machine learning techniques, including generalized linear models (GLMs), gradientboosting, and deep learning, to extract insights from large, complex datasets. Work with data engineers to ensure the ingestion, transformation, and deployment of More ❯
learning and statistical techniques, along with wider analytical approaches such as time series and analytics with unstructured data (e.g., NLP). They recently used gradientboosting machine learning to predict radio listening behaviour for a client, taking into account advertising spend. The Successful Candidate Is Likely To Have More ❯
learning and statistical techniques, along with wider analytical approaches such as time series and analytics with unstructured data (e.g., NLP). They recently used gradientboosting machine learning to predict radio listening behaviour for a client, taking into account advertising spend. The Successful Candidate Is Likely To Have More ❯
Hook, Hampshire, United Kingdom Hybrid / WFH Options
360 Resourcing Solutions
to the team. You'll have great technical understanding of various machine learning approaches, which would include regression methods, probabilistic pricing models, tree based gradientboosting approaches, information theory, neural networks, transfer learning, etc. While your focus will be primarily on the Valuations and Pricing Team you'll More ❯
communicate insights to non-technical audiences. Requirements: Strong knowledge of statistical modeling techniques, especially Generalized Linear Models (GLMs) Familiarity with machine learning methods, particularly GradientBoosting Models (GBMs) Demonstrated experience working with large datasets Proficient in Python, SQL, SAS, or similar programming languages Experience with Willis Towers Watson More ❯
london, south east england, united kingdom Hybrid / WFH Options
Arthur Recruitment
communicate insights to non-technical audiences. Requirements: Strong knowledge of statistical modeling techniques, especially Generalized Linear Models (GLMs) Familiarity with machine learning methods, particularly GradientBoosting Models (GBMs) Demonstrated experience working with large datasets Proficient in Python, SQL, SAS, or similar programming languages Experience with Willis Towers Watson More ❯