Credit Risk Modelling Consultants London £60,000 - £80,000 As an Analytics Consultant, you'll be part of a fast-growing team working on a wide variety of projects across predictive modelling, optimization, regulatory compliance and big data using the latest tools and techniques. The team is responsible for the delivery ofall analytic offerings to clients across within Europe, Middle East and Africa (EMEA), and some projects may require substantial time spent on client site, so you should be willing to travel (around 30%). The role involves working closely with clients and internal teams to deliver high quality, end-to-end analytical solutions that create strong business impact. Responsibilities Design and develop state-of-the-art, data-driven exploratory analysis as well as predictive and optimisation / decision models to solve business problems across different industries including auto, financial services, retail, insurance, manufacturing, utilities. Build and evaluate predictive and optimisation / decision models to be deployed in production systems. This includes the analysis of large amounts of historical data, determining suitability for modelling, data clean-up and filtering, pattern identification and variable creation, selection of sampling criteria and performance definition, and variable selection, and experiments with different types of algorithms and models, analysing performance, to identify the best algorithms to employ. Provide consulting support to customers for interpretation and effective usage of models and strategies, and regulatory analytics and processes. Work simultaneously on a number of different projects of varying complexity and length. Skills & Experience Advanced degree in operational research, mathematics, statistics, engineering, physics or similar technical field. Core analytics experience, including experience with an IRB bank or financial institution. Knowledge and interpretation experience of regulatory and governance requirements for financial institutions, particularly relating to Basel II and IFRS9. Hands-on experience of analytics across the Customer Risk Life Cycle (Collections, Origination and Portfolio Management) and regulatory modelling (Basel II and IFRS9) in retail banking. Strong analytic and problem solving skills, especially in the area of predictive modelling. Hands-on experience with building models using SAS, R, Python etc... nowledge of: scoring technology and methodologies; model development techniques and tools; advanced statistical methods and quantitative analysis; statistical tools and programs; familiarity with Java and/or C++ or other similar object oriented programming language. An excellent communicator with the ability to explain complex concepts and describe technical material to non-technical users. Fluency in English.