3 of 3 Permanent Random Forest Jobs in Manchester

tuning and deploying machine learning methods Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in DevOps and Azure ML, or other MLOps and ML Lifecycle technology stacks, such as AWS, Databricks, Google ...

tailored to the needs of varied audiences. Expertise in the application of several supervised and unsupervised machine learning techniques such as classification (e.g. Random Forests, Support Vector Machine), regression (e.g. Ridge Regression, Lasso), dimensionality reduction (e.g. Principal Components Analysis, t-SNE) and clustering (e.g. KMeans, Hierarchical Clustering). Desirable ...

experience Previous experience within data science Experience in insurance pricing and modelling Experience and detailed technical knowledge of GLMs/Elastic Nets, GBMs, GAMs, Random Forests, Neural Networks and clustering techniques Knowledge of statistics and distributions commonly used in insurance Experience in programming languages (e.g. Python, PySpark ...