3562971-Manager

Qualifications:    Master's degree in economics, mathematics, engineering,  operations research or related areas is preferred; candidates with BA/BS degrees from the top tier academic institutions are also welcome to apply 4 - 10 years of experience in credit risk modelling/ analytics preferably in Banking and Financial Services.  ( Experience in US banking domain is a plus) Hands-on experience working on Machine Learning models to solve analytical use cases. Experience with credit risk models like PD, customer management models, EAD, LGD, loan management, underwriting models, collection models . Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results. Proficiency in some of the key programming languages such as Python, PySpark, Advance SQL, Hive and experience with ML related libraries. Experience with large-scale data/ Big data processing and distributed computing frameworks is a plus. Strong communication skills, both written and verbal, with the ability to convey complex ideas to diverse stakeholders Responsibilities: Design, implement, and optimize sophisticated machine learning models in Banking domain for Credit Risk modeling. Your work will enable us to uncover meaningful patterns, trends, and insights from data, ultimately solving analytical use cases. Utilize sophisticated algorithms and methodologies to refine and improve the performance of credit risk/ marketing mix models, enabling accurate predictions and actionable outputs for analytical use cases. Stay updated on the latest machine learning advancements, actively identifying and integrating cutting-edge techniques to continuously improve our models and address diverse analytical use cases. Provide data-driven insights and recommendations that support decision-making processes and enable us to overcome analytical hurdles. Document your methodologies, experiments, and results in clear and concise terms. Effectively communicate complex concepts and findings to both technical and non-technical stakeholders. Stay informed about the latest advancements in machine learning (ML) and assist in identifying and adopting cutting-edge techniques. Enable us to continuously enhance our ML models and effectively address diverse analytical use cases.  About the TeamEXL is the indispensable partner for leading businesses in data-led industries such as insurance, banking and financial services, healthcare, retail and logistics. We bring a unique combination of data, advanced analytics, digital technology and industry expertise to help our clients turn data into insights, streamline operations, improve customer experience, and transform their business. Our partnerships with clients are built on a foundation of collaboration – and we’ve been chosen as a partner by nine of the top ten leading US insurance companies, nine of the top 20 global banks, and six of the top ten US health care payers. We function as one team to make your goals our goals, whether that’s unlocking the value of generative AI or embedding analytics into workflows that reduce risk or power your growth. Clients choose EXL as their transformation partner for many reasons. Our geographic diversity make talent all over the world instantly accessible. Digital accelerators enable unmatched speed-to-value, letting you realize results fast. It’s our people that truly set us apart, though, including the 1,500 data scientists we have dedicated to our generative AI practice. And our more than twenty years of experience in delivering business services, garnering stellar client references, and maintaining a solid balance sheet are reassuring to our C-suite clients. Find out for yourself why clients, employees, and analysts think we’re some of the best in the business. Contact us to see how we can help you achieve your goals.