6 of 6 Gradient Boosting Jobs in London

trends and competitor behaviours to build predictive models that inform pricing strategy. Apply advanced statistical and machine learning techniques, including generalized linear models (GLMs), gradient boosting, 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), gradient boosting, 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 gradient boosting 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 gradient boosting machine learning to predict radio listening behaviour for a client, taking into account advertising spend. The Successful Candidate Is Likely To Have 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 Gradient Boosting Models (GBMs) Demonstrated experience working with large datasets Proficient in Python, SQL, SAS, or similar programming languages Experience with Willis Towers Watson 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 Gradient Boosting Models (GBMs) Demonstrated experience working with large datasets Proficient in Python, SQL, SAS, or similar programming languages Experience with Willis Towers Watson More ❯