Evalueserve is a global leader in delivering innovative and sustainable solutions to a diverse range of clients, including over 30% of Fortune 500 companies. With presence in more than 45 countries across five continents, we excel in leveraging state-of-the-art technology, artificial intelligence, and unparalleled subject matter expertise to elevate our clients business impact and strategic decision-making. We have 4,500+ talented professionals operating across 45 countries, including India, China, Chile, Romania, the US, and Canada. Our global network also extends to emerging markets such as Colombia, the Middle East, and the rest of Asia-Pacific. Recognized by Great Place to Work in India, Chile, Romania, the US, and the UK in 2022, we offer a dynamic, growth-oriented, and open culture that prioritizes flexible work-life balance, diverse and inclusive teams, and equal opportunities for all. About Risk and Quant Solutions (RQS) Risk and Quant is one of the fastest growing practices at Evalueserve. As an RQS team member, you will address some of the world's largest financial needs with technology proven solutions. You would solve these banking challenges and improve decision making with award winning solutions. What you will be doing at Evalueserve: The candidate will be working directly with the client on credit risk models for a global investment bank with which we have an existing relationship. As a first assignment, the candidate will be working with model development team of the bank and will work with them to improve the existing models. The role requires good understanding of credit risk models for retail and wholesale portfolio, model structure, variable treatments, variable data framework and process efficiency in model development process. Important responsibilities in this role will include: The candidate needs to have a good knowledge of statistical methods and tools including linear and logistic regression. Knowledge of machine learning and time- series models will be an added advantage. Understanding of credit risk model constructs and different credit risk modeling frameworks. Experience of working with PPNR, stress testing, CCAR, DFAST and time-series models Understanding of the consumption layer of the curated data, ie. Model development for credit risk models, especially PPNR, Stress testing, and Scorecards Understanding of variables treatments, exclusions, transformations and data sources Ability to work directly with client with no handholding Model development/ Model Validation experience using SAS or Python Adhoc data analysis and queries to support questions and process migration Prototype source data migration in established processes and production codes Help build competencies and develop training programs in credit risk Excellent communication skills and team player Sense of urgency and time constraints Skill Set Required Knowledge of Credit Risk Models PPNR, Stress testing, CCAR, DFAST, Scorecards, PD, EAD, and LGD, CECL, IFRS 9, Basel II IRB approach for Credit Risk, Logistic and Linear Regression Models Strong experience in the credit risk model development from the scratch. Good knowledge of SAS or Python Experience working with multiple datasets, cleaning of data, and performing data analysis. Excellent verbal and written communication abilities Ability to articulate ideas and develop recommendations Experience in working as a part of bigger teams working towards a common goal Proficiency in developing and giving presentations Strong client presentation skills 4+ years of experience in Global Banks Strong analytical and interpersonal skills Education & Experience Statisticians/ Econometricians/Engineers with finance background