4 of 4 Permanent Random Forest Jobs in London

quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, or similar Working knowledge of statistical and machine learning methods (e.g. logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command ...

working with real world, messy data and delivering production ready solutions. Familiarity with cloud environments such as AWS is beneficial. Exposure to Bayesian methods, random forests, or marketing analytics is advantageous but not essential. Ability to demonstrate how your work has delivered tangible value or influenced decision making. What ...

data science projects and demonstrating commercial impact. Familiarity with cloud environments such as AWS is beneficial. Exposure to Bayesian methods, random forests, or similar approaches is highly desirable. Marketing or channel performance experience is helpful but not essential; technical capability is the priority. What They Offer Salary between ...

Experience in financial markets, algo-trading, or prediction market platforms (Polymarket, Manifold, etc.) Quantitative background in maths, statistics, or probability theory ML experience including random forests, regression models, scikit-learn, and PyTorch AWS infrastructure experience deploying containerised applications and managing cloud environments (EC2, Lambda, RDS) Open-source contributions ...