18 of 18 Permanent Random Forest Jobs in the UK

complex analytical and technical content ● 3-6 years of relevant experience with classical descriptive statistics, standard statistical modelling (e.g. advanced regressions, clustering, classification models) and machine learning techniques (e.g. random forest, support vector machines, gradient boosting, XGBoost) ● Programming experience in the following languages: Python and SQL ● Experience in leading complex engagements to deploy advanced analytics and data science More ❯

Gen AI and machine learning. Experience analyzing large data sets, data cleaning, and statistical analysis. Proven experience with at least three machine learning algorithms (e.g., neural networks, logistic regression, random forests). Proficiency with Java and Python, understanding of data structures, algorithms, and software design patterns. Experience with AI/Gen AI frameworks like TensorFlow or PyTorch. Experience with More ❯

Develop scalable tooling to support our research and analytics teams-from data pipelines to custom dashboards. Lead the development and deployment of advanced modelling techniques (e.g. multilevel regression, segmentation, random forest models, text analysis). Collaborate with the wider team on bespoke research and client projects, offering analytical expertise where needed. Help shape our codebase and analytics infrastructure 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 ❯

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 ❯

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 ❯

of biases. Proficiency in documenting methodologies. Familiarity with version control tools like GitHub. Experience building machine learning pipelines and understanding engineering principles. Knowledge of machine learning techniques such as Random Forest and LGBM. About us: Prevail Partners provides intelligence, research, and consultancy services to clients across Europe, the Middle East, and Africa, working with governments, corporations, and NGOs. More ❯

and sharing methodologies with data professionals. Familiar with version control tools like GitHub. Familiar with building machine learning pipelines and basic engineering principles. Familiar with machine learning techniques (e.g. Random Forest and LGBM). Us: Prevail Partners delivers high quality intelligence, research and consultancy services to clients ranging from governments and multinational corporations to non-governmental organisations. These 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 ❯

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 ❯

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 ❯

skills using tools like Tableau, Spotfire, Power BI etc. Strong SQL skills required Experience in Python with predictive modelling, regression techniques as well as wider techniques like clustering/random forest is desirable Tech Stack: SQL, Python, R, Tableau, AWS Athena + More! More information: Enjoy fantastic perks like private healthcare & dental insurance, a generous work from abroad More ❯

Previous experience within data science Experience in commercial pricing and modelling, ideally with a focus in Motor Experience and detailed technical knowledge of GLMs/Elastic Nets, GBMs, GAMs, Random Forests, and clustering techniques Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Proficient at communicating results in a concise manner both verbally and written Behaviours: Motivated by More ❯

Previous experience within data science Experience in commercial pricing and modelling, ideally with a focus in Motor Experience and detailed technical knowledge of GLMs/Elastic Nets, GBMs, GAMs, Random Forests, and clustering techniques Experience in programming languages (e.g. Python, PySpark, R, SAS, SQL) Proficient at communicating results in a concise manner both verbally and written Behaviours: Motivated by More ❯

of applying NLP expertise is of crucial importance to this hire. Head of Data Science : - Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, Random Forests, etc. - Experience with common data science toolkits, such as Python - Proficiency in using query languages such as SQL on a big data platform e.g. Hadoop, Hive - Good applied More ❯

companies in fraud/risk control functions • Coding skills in one of the modern languages Java, Python, Scala • Experience/knowledge of advanced machine learning techniques such as GBM, random forest • Candidate has demonstrated the ability to begin solving complex investigations or escalations by diving deep to get to the root cause post considering all possible scenarios • Candidate More ❯

Spring & Spring Boot, Java, Python, FastAPI Frontend: Vue.js Cloud: AWS Databases: Elasticsearch & Postgres And more This role offers exciting opportunities to dive into various areas, including Natural Language Processing, Random Forest and Monte Carlo Simulations, Classification, Big Data ETL Pipelines, High Volume Event Processing, Predictive Analysis, CI/CD Cloud Ops, Mentoring, UX Design, Data Visualization, and Build More ❯

Spring & Spring Boot, Java, Python, FastAPI Frontend: Vue.js Cloud: AWS Databases: Elasticsearch & Postgres And more... This role offers exciting opportunities to dive into various areas, including Natural Language Processing, Random Forest and Monte Carlo Simulations, Classification, Big Data ETL Pipelines, High Volume Event Processing, Predictive Analysis, CI/CD Cloud Ops, Mentoring, UX Design, Data Visualization, and Build More ❯