3 of 3 Permanent Random Forest Jobs in London

such as GraphRAG and agentic RAG to reduce hallucination and improve factual grounding. Technical Proficiency Machine learning algorithms: linear regression, logistic regression, decision trees, random forests, support vector machines, neural networks Data science tools: NumPy, SciPy, Pandas, Matplotlib, TensorFlow, Keras Cloud computing platforms: AWS, Azure, GCP Natural language processing ...

cloud‐based machine learning services using one or more cloud providers (preferably GCP). Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.). Strong knowledge of SQL and Python’s ecosystem for data ...

throughout.* Sound statistical and analytical foundations (probability theory, GLMs, time series analysis) and comprehensive understanding of modern machine learning techniques and modelling approaches (e.g. random forest, XGBoost, GBMs).* Experience working with complex, sparse, or imperfect datasets.* Solid SQL, data handling and data visualisation skills.Soft Skills* Ability ...