4 of 4 Permanent Cluster Analysis Jobs in England

of analytical projects using CRA data assets, including credit strategy and model development, ensuring they meet quality standards and deadlines. This encompasses all phases, such as sample design, retrospective analysis, performance analysis, population split 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 develop solutions for internal and external clients. Present proposals, methodologies, and results to stakeholders, explaining complex statistical techniques to diverse audiences, including … a STEM field. Experience with credit bureau data needed. 6 + years of experience in a credit risk/model development environment. Previous consultancy experience is desirable. Strong data analysis skills. Excellent written and verbal communication skills. THE BENEFITS Up to £80,000 salary. Discretionary bonus. Pension scheme. Hybrid working model. HOW TO APPLY Please register your interest by More ❯

of analytical projects using CRA data assets, including credit strategy and model development, ensuring they meet quality standards and deadlines. This encompasses all phases, such as sample design, retrospective analysis, performance analysis, population split 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 develop solutions for internal and external clients. Present proposals, methodologies, and results to stakeholders, explaining complex statistical techniques to diverse audiences, including … a STEM field. Experience with credit bureau data needed. 6 + years of experience in a credit risk/model development environment. Previous consultancy experience is desirable. Strong data analysis skills. Excellent written and verbal communication skills. THE BENEFITS Up to £80,000 salary. Discretionary bonus. Pension scheme. Hybrid working model. HOW TO APPLY Please register your interest by More ❯

of analytical projects using CRA data assets, including credit strategy and model development, ensuring they meet quality standards and deadlines. This encompasses all phases, such as sample design, retrospective analysis, performance analysis, population split 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 develop solutions for internal and external clients. Present proposals, methodologies, and results to stakeholders, explaining complex statistical techniques to diverse audiences, including … a STEM field. Experience with credit bureau data needed. 6 + years of experience in a credit risk/model development environment. Previous consultancy experience is desirable. Strong data analysis skills. Excellent written and verbal communication skills. THE BENEFITS Up to £80,000 salary. Discretionary bonus. Pension scheme. Hybrid working model. HOW TO APPLY Please register your interest by More ❯

mindset with problem-solving skills and passion for big data. Experience building multi-dimensional data models. Experience with distributed data systems for large datasets. Proficiency in regression, classification, and cluster analysis. Knowledge of data visualization/reporting software (e.g., Tableau). Advanced SQL, data mining skills, and analytical tools (R/Python/SAS). We are committed to More ❯