assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
leeds, west yorkshire, yorkshire and the humber, united kingdom
Ventula Consulting
assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
assets. This includes credit strategy and model developments to the required quality standards and timescales. This will cover all stages, including sample design, retrospective analysis, performance analysis, population split analysis and reject analysis. Develop deep data knowledge in the structure, application and permissible use of data sources … across consumer, commercial and open banking lines of business Application of statistical techniques (including Regression techniques, Machine Learning techniques, Decision Trees, CHAID Analysis & ClusterAnalysis) to solve business problems. Application of data mining tools and programming languages Python and SQL to prepare data, undertake analysis and More ❯
working in partnership with their team of CRO Analysts, Developers, and UX/UI team every day. General Day to Day Duties: 1. Data Analysis Use web and web optimisation tools like Adobe Target, Medallia MXO, Medallia Decibel or similar. Use web analytics to analyse current web performance, journeys … campaign, channel, and content performance. Identify the inter-relationships and connections in visitor behaviours that fuel engagement, conversion, and new optimization opportunities. Supplement web analysis with SEO and Social Listening to add context, drivers, and identify further opportunities. Work with our Data Science team to brief deeper, more involved … analysis using raw GA4 data to create data platforms to support personalisation and optimisation, and deeper insights to drive optimisations e.g. clusteranalysis, content pathways, journey mapping, personalisation opportunities, etc. Create and maintain reports to track the success of optimisations. 2. Conversion Rate Optimisation - Insight and Opportunity More ❯
of Data Science/Machine Learning would be useful. We use a range of predictive analytics and machine learning methodologies, including logistic regression and clusteranalysis, plus some predictive time series analysis. More ❯
modelling for a variety of projects across different industries. You will do this by: Owning the analytics workstreams for major research projects including segmentation analysis, factor reduction, multi-level regression modelling. Setting best-practice and standards, processes for analytics including segmentation. Automating common analytical tasks particularly for trackers and … different types of statistical analyses, including factor reduction techniques, multi-level/mixed-effect regression (linear and logistic at a minimum), and segmentation/cluster analysis. Ability to run exploratory data analysis, enjoys using creative ways of looking for patterns and nuggets hidden in the data. Deep experience … candidate will also have worked with publicly available datasets (e.g., census or other ONS data). Strong proficiency in R or Python for data analysis and data visualisation. Nice to have The ideal candidate has experience in using both frequentist and Bayesian approaches. Understanding of the full market research More ❯
