1 to 5 of 5 Permanent Random Forest Jobs in London

parameter estimation, factors selection, PCA, hypothesis testing, time series, queuing theory, survival analysis, clustering, linear programming. Experience with machine learning methods, such as regularization, random forests, neural networks and deep learning. Ability to write algorithms and implement pipelines in Python. Knowledge of Scala, R, is a plus. Experienced in more »

Possess vast experience and expertise of working with probability and statistics, inclusive of machine learning, experimental design, and optimisation Experience using Gradient Boosting Machines, Random Forest, Neural Network or similar algorithms Proven and successful track record of leading high-performing data analyst teams through the successful performance of more »

Possess vast experience and expertise of working with probability and statistics, inclusive of machine learning, experimental design, and optimisation Experience using Gradient Boosting Machines, Random Forest, Neural Network or similar algorithms Proven and successful track record of leading high-performing data analyst teams through the successful performance of more »

GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. Proven knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. more »

GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. Proven knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. more »