13 of 13 Remote Random Forest Jobs in the UK

and manage deliverables Qualifications Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL and 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 ❯

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 ❯

ongoing don't miss your chance to secure the future of your career! Contact me @ (url removed) or on (phone number removed). 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 ❯

and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal More ❯

and understanding of statistical methods such as time to event analysis, machine learning, meta-analysis, mixed effect modeling, longitudinal modeling, Bayesian methods, variable selection methods (e.g., lasso, elastic net, random forest), design of clinical trials. Strong programming skills in R and Python. Demonstrated knowledge of data visualization, exploratory analysis, and predictive modeling. Excellent interpersonal and communication skills (verbal More ❯

the risk models and working closely with underwriting and technical modelling teams. ✔️ Personal Lines Pricing experience (Motor, Home or Pet) ✔️ Strong skills in predictive modelling – e.g., GLMs, GBMs, GAMs, Random Forests ✔️ Proficiency in R, Python, PySpark, SAS or SQL ✔️ Experience with Radar and/or Emblem ✔️ A numerate degree (e.g., Maths, Stats, Actuarial, Engineering) ✔️ Strong communication and stakeholder management More ❯

the risk models and working closely with underwriting and technical modelling teams. ✔️ Personal Lines Pricing experience (Motor, Home or Pet) ✔️ Strong skills in predictive modelling – e.g., GLMs, GBMs, GAMs, Random Forests ✔️ Proficiency in R, Python, PySpark, SAS or SQL ✔️ Experience with Radar and/or Emblem ✔️ A numerate degree (e.g., Maths, Stats, Actuarial, Engineering) ✔️ Strong communication and stakeholder management More ❯