7 of 7 Permanent Random Forest Jobs in England

robust and do not suffer from issues such as multicollinearity, overfitting, data leakage etc. Have knowledge of advanced machine learning algorithms such as random forest, gradient boosting, and support vector machines Experience in feature engineering and selection techniques Understanding of model evaluation metrics and cross-validation techniques ...

regression, ranking) Analyse financial, credit, and time-series data to extract predictive signals Build and benchmark models such as: Gradient boosting (XGBoost, LightGBM, CatBoost) Random Forests Logistic/linear regression Design LLM-powered workflows for: Document understanding (loan docs, credit memos, financials) Risk factor extraction Deal-level reasoning ...

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 ...

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 ...

feeds. ● Predictive Modeling: Deep proficiency with the PyData stack (pandas, numpy, scikit-learn, XGBoost) and advanced machine learning methods including neural networks and random forests. ● Analytical Domain Knowledge: A professional-level understanding of cricket match dynamics and the factors influencing match state outcomes. Nice-to-haves ● Tracking Data Experience ...

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 ...

solve problems Good experience in Python, NodeJS, ReactJS, Java Agentic Framework experience is an added advantage Experience using LLMs, ML algorithms of NLP, random-forest or other algos Experience in design, implementation, or consulting in applications and infrastructures experience Experience in SQL and noSQL Databases ...