Responsibilities
*Partner with business and functional teams to understand problem statements and translate them into analytical and machine learning solutions
*Apply end-to-end data science methodology, including business understanding, data collection, data preparation, exploratory data analysis, feature engineering, model development, validation, deployment support, monitoring, and continuous improvement
*Design, develop, validate, and enhance statistical, predictive, machine learning, optimization, and segmentation models
*Deliver data-driven use cases across key banking domains such as Credit Risk, Financial Crimes, Operations, Marketing, and Customer Serviceal or Finance* or bank* or Money or AML)
Qualifications
*Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science,
*Min 4+ years of Experience in Data Science,
*Engineering, Economics, or a related quantitative discipline
*Relevant professional experience in data science, advanced analytics, or machine learning
*Experience in banking, fintech, or financial services is strongly preferred
Technical Skills and Competencies
*Strong knowledge of statistics, machine learning, predictive modelling, and data science methodologies
*Hands-on experience in Python and SQL for data analysis, modelling, and solution development
*Exposure to model deployment, model monitoring, and lifecycle management is an advantage
Understanding of model governance, documentation standards, and explainability requirements in regulated environments
*Experience working with structured and large datasets in enterprise environments
*Knowledge of data visualization and storytelling techniques is preferred
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