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Key Responsibilities: Model Development: Design, build, and deploy advanced propensity models, credit risk models, and other statistical models to address various business challenges within the banking domain. Data Analysis: Conduct in-depth analysis of large and complex datasets to identify trends, patterns, and anomalies. Analytical Solution: Develop and implement analytical solutions for banking operations, including customer segmentation, fraud detection, and performance optimization. Collaboration: Work closely with business stakeholders, data engineers, and other teams to understand business requirements and deliver effective data-driven solutions. Reporting: Present findings and model performance to both technical and non-technical audiences in a clear and concise manner. Innovation: Stay updated with the latest advancements in data science, machine learning, and the banking industry to propose and implement innovative solutions. Qualifications: ● Experience : Minimum of 5 years of professional experience as a Data Scientist, with a significant focus on the banking or financial services industry. ● Technical Skills : Good understanding on building performance dashboards, sales models (propensity, segmentation, income proxy), credit models (A-score, B-score) Proficiency in programming languages such as Python or R. Strong knowledge of machine learning algorithms (e.g., classification, regression, clustering). Experience with SQL and database management. Hands-on experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, Scikit-learn). Familiarity with big data & cloud technologies is a plus. ● Industry Knowledge : Proven experience in building and deploying models for credit risk, propensity modeling, or other relevant banking analytics projects. ● Soft Skills : Excellent problem-solving and analytical skills. Strong communication and presentation abilities. Ability to work independently and as part of a team in a fast-paced environment. This position will be assigned to an FSI client's project.
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