5 of 5 Remote Gradient Boosting Jobs

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 ❯

to the team. You'll have great technical understanding of various machine learning approaches, which would include regression methods, probabilistic pricing models, tree based gradient boosting 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 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 ❯