1 to 25 of 28 Permanent Random Forest Jobs in the UK excluding London

of two days a week from our Chester head office Team: Data and Analytics Reports to: Data Science Manager About Us The Forge Holiday Group encompasses Sykes Holiday Cottages, Forest Holidays, UKcaravans4hire and Bachcare in New Zealand. We unite under four core company values that serve as the foundation of everything we do: Being One Team, Owning It, Communicating … our Customers, Owners and Colleagues alike. Essential Experience: Extensive experience designing, developing and deploying machine learning and AI solutions in production environments Statistical modelling, machine learning (e.g. logistic regression, random forest, XGBoost, and modern deep learning techniques (e.g. transformers, transfer learning, reinforcement learning) Proven ability to lead technical direction across projects or domains Expertise in model validation, explainability More ❯

tolerant code using Python and SQL, and champion best practices like code reviews, pair programming, and knowledge- sharing sessions. Apply robust ML and statistical techniques ( from classical models like Random Forest to state- of- the- art NLP and LLMs) to solve complex problems across multiple domains. Collaborate closely with stakeholders, ensuring technical solutions are well- communicated and drive More ❯

tolerant code using Python and SQL, and champion best practices like code reviews, pair programming, and knowledge- sharing sessions. Apply robust ML and statistical techniques ( from classical models like Random Forest to state- of- the- art NLP and LLMs) to solve complex problems across multiple domains. Collaborate closely with stakeholders, ensuring technical solutions are well- communicated and drive More ❯

above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with a preference for SQL and Python. Familiarity with large language models and prompt engineering would be More ❯

above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with a preference for SQL and Python. Familiarity with large language models and prompt engineering would be More ❯

above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with a preference for SQL and Python. Familiarity with large language models and prompt engineering would be More ❯

processing of and cleaning of data, merging/joining disparate data sources, feature engineering, performing analyses and communicating results). Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks etc.) and assess the relative strength of each model Identify which factors are relevant and predictive and should be included in the model build Document More ❯

Mining, Data Quality, Data Visualization, Deep Learning, Graph Algorithms, High-Performance Computing, Logistic Regression Model, Machine Learning (Ml), Master Data Management, Pandas (Python), Python (Programming Language), R (Programming Language), Random Forest Algorithm, Sql (Structured Query Language), Statistical Modeling, Time Series Analysis More ❯

AI, or a related discipline. Strong numerical and statistical knowledge (e.g. Bayesian/frequentist methods, probability distributions). Solid understanding of machine learning algorithms (e.g. linear/logistic regression, random forests, neural networks, time series models). Experience with multiple programming languages — with Python and SQL preferred. Interest or familiarity with large language models and prompt engineering (desirable). More ❯

machine learning to real-world problems. Experience translating customer requirements into quantitative models. Experience in one or more of the following technical disciplines: Natural Language Processing (NLP) ML (e.g., Random Forests, CatBoost, LXGM) Image Recognition Optical Character Recognition (OCR) Motion Capture Proficiency in Python, R, or C++, including relevant libraries (numpy, pandas, matplotlib, scikit-learn, tensorflow, etc.). Proficiency More ❯

requirements. Key Skills and Experience: Previous experience within general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

requirements. Key Skills and Experience: Previous experience within general insurance pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

Skills and Experience: Previous experience within Personal Lines Pricing is advantageous Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering Experience in statistical and data science programming languages (e.g. R, Python, PySpark, SAS, SQL) A good quantitative degree (Mathematics, Statistics, Engineering, Physics, Computer Science More ❯

knowledge of current trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical and data science More ❯

knowledge of current trends and issues in motor or home pricing Experience with some of the following predictive modelling techniques; Logistic Regression, GBMs, Elastic Net GLMs, GAMs, Decision Trees, Random Forests, Neural Nets and Clustering. Knowledge of the technical differences between different packages for some of these model types would be an advantage. Experience in statistical and data science More ❯

e.g. Power BI). Microsoft suite - Excel, Powerpoint etc. Languages: Python, SQL, Git. Working towards more complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), Principal Component Analysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and More ❯

e.g. Power BI). Microsoft suite - Excel, Powerpoint etc. Languages: Python, SQL, Git. Working towards more complex modelling of the data using innovative methods. Knowledge of Machine Learning: Classification (Random Forest, Decision Trees, KNN), Regression. Modelling (linear, sparse, logistic), Principal Component Analysis (PCA, PCR), clustering (K-means). Profile: Strong analytical skills, ability to generate strong insights and More ❯

enterprise ML products. Expertise in Mathematical Optimization: linear programming (LP), quadratic programming (QP), and mixed-integer programming (MIP). Proficiency in Machine Learning models, including time-series forecasting, clustering, random forest, and deep learning. Hands-on experience with solvers like Gurobi, CPLEX, SCIP, or GLPK. Familiarity with Agile methodologies such as Scrum or Kanban. Preferred Skills Strategic thinking More ❯

Have: Financial Services Experience Interviews ongoing don't miss your chance to secure the future of your career! Contact me @ or on . Data Science, Data Scientist, AI, ML, Random Forest, Databricks, SageMaker, Regression, Gradient Boosting, NLP, Palantir, Insurance, Banking More ❯

working to support the senior data modeller in creating, developing, and iteratively improving models based on historic trends. The models will vary in design, but current models include XGboost, Random Forest and MCMC models. This role will also create analysis and provide support to the pricing team, to increase their automation and accuracy of analysis in the financial … that benefit both customers and clients. The Person Experience of using machine learning techniques on real data is needed for this role. Desirable if the candidate has experience of random forests, XGboosts or Monte Carlo. Proficiency in Python for data manipulation and model development. Otherwise, proficiency in another language (such as R, Java etc) with the ability to learn More ❯