3 of 3 Random Forest Jobs in London

plus to manipulate data and draw insights from large data sets Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc. Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling ...

Expertise: Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, BERT, LSTM, NLP, Transfer Learning). Reasonable Adjustments: Respect and equality are core values to us. We are proud ...

/or product portfolios, ideally within Motor (Commercial Vehicle preferred). Strong modelling background (such as): GLMs, GBMs, GAMs, Elastic Net, Trees/Random Forests, Neural Nets, Clustering . Strong coding capability in Python/PySpark/R/SAS/SQL . Experience with WTW Radar. Confident communicator. ...