13 of 13 Customer Analytics Jobs in the North of England

TITLE: Loans Performance Analytics Senior Analyst - 12 Month FTC SALARY: The salary banding is £39,825 - £44,250 LOCATION: Chester, Edinburgh, Leeds, Newport HOURS: 35 hours, full time WORKING PATTERN: Our work style is hybrid, which involves spending at least two days per week, or 40% of our time … opportunity to influence the strategic direction of the UKs largest consumer finance provider. You'll be responsible for leading the team to optimise individual customer pricing across our four brands - Lloyds, Halifax, BoS and MBNA - and via our own and third-party digital channels, delivering fair value for customers ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...

extraction Create deterministic problems with reproducible answers - avoid stochastic elements or require fixed random seeds for exact reproducibility Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency Design end-to-end problems spanning the complete data science pipeline (data ingestion … standard data science libraries and statistical methods Document problem statements clearly with realistic business contexts and provide verified correct answers Problem Domains (Examples) Business Analytics & Predictive Modeling Customer segmentation, churn prediction, and CLV modeling algorithms Fraud detection with precision-recall optimization A/B test statistical calculations ...