Job Description: Responsibilities:Large data management, feature engineering, strong hands on in EDA and feature Engineering using bureau data in banking domain ;Good to have - Design, implement, and optimize sophisticated machine learning models in Banking domain for Credit Risk modeling. ;Create Python classes and functions to automate EDA and Feature Transformation processStay 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. ;Qualifications:4 - 10 years of experience in credit risk analytics preferably in Banking and Financial ServicesA minimum of 3 years of hands-on experience working on Machine Learning models to solve analytical use cases.Experience with bureau data; feature engineering ;Excellent problem-solving and analytical skills, with the ability to work on complex projects and deliver high-quality results.Proficiency in Python programming languages is mustExperience with large-scale 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
