5 of 5 Remote Decision Tree Jobs in London

Key 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 More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

analysis, and reject analysis. Develop extensive knowledge of data structures, applications, and permissible uses across consumer, commercial, and open banking sectors. Apply statistical techniques (e.g., regression, machine learning, decision trees, CHAID analysis, and cluster analysis) to address business challenges. Utilise data mining tools and programming languages such as SAS, SQL, and Python to prepare data, perform analyses, and More ❯

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech . We are … think about fraud detection as a wider team Responsibilities: You will be part of a team that builds, evaluates and deploys machine learning models to improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for … related domain Experience working with large-scale, high-dimensional, and heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to More ❯