An opportunity to be part of a cutting-edge analytics team, using data and analytics to guide business decisions to achieve success. Joining a sector market-leader you'll work in a team of 50 analysts in delivering advanced analytics solutions. The Role * Successfully contribute and deliver to the advanced environment of analysts to accurately value portfolios for investment and increase profit on previous purchases. * Use machine learning and advanced analytical techniques (KNN, XGBoost, etc.) to increase prediction accuracy * Continuously improve existing models and create new tools/models for analysis and valuate potential accounts / portfolios. Test and validate results. * Present and explain valuations and predictions to Investment Committee and Stakeholders * Dig into data and raw information through statistical analysis to discover trends and patterns that can be used to extract valuable business insights. * Develop predictive models, e.g. Scorecards, using statistical tools and techniques. * Contribute to internal Analytical Labs to keep pushing the boundaries in modelling, predictive analytics and business insights whilst taking advantage of the latest developments in Data Science and analytics. Candidate Profile * Significant experience (2 years +) working with large data sets and using quantitative analysis/modelling to drive business results. * Experience in using statistical computing languages R, Python or SAS to manipulate data and draw insights from those data sets. * Experience with databases (SQL) would be beneficial. * Strong problem-solving and creative skills and the ability to exercise sound judgment and make decisions based on accurate and timely analyses. * Experience and interest in model development. * High level of integrity and dependability with results-orientation and a strong sense of urgency. Thorough understanding of quantitative analysis preferably from banking and finance industry. * Ability to communicate and interact with various people at all levels and to present your findings, i.e. be able to explain complex problems in an easy way to non-analysts.