Data Scientist Assistant Manager
2 days ago
Key Responsibilities:
• Develop and implement statistical models and machine learning algorithms to support financial decision-making (e.g., credit scoring, risk modeling, customer behavior prediction).
• Analyze large and complex datasets from multiple sources to identify business opportunities and operational risks.
• Collaborate with business units (Risk, Marketing, Collections, Product) to translate analytical insights into actionable strategies.
• Develop and maintain predictive models and machine learning algorithms for key financial applications such as credit scoring, risk assessment, fraud detection, and customer behavior analysis.
• Design, test, and monitor model performance to ensure accuracy, stability, and compliance with internal and regulatory standards.
• Develop dashboards and reports to visualize key metrics and communicate findings effectively to non-technical stakeholders.
• Work closely with Data Engineers to ensure data quality, structure, and availability for modeling and analytics.
• Stay updated with the latest techniques in data science, AI/ML, and financial analytics to continuously improve analytical capabilities.
Qualifications:
• Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Economics, Mathematics, or a related field.
• Minimum 5 years of experience in data science or analytics, with at least 2 years in a leadership or project management role.
• Strong proficiency in Python, R, SQL, and experience with data visualization tools such as Tableau or Power BI
• Experience working with large-scale structured and unstructured datasets.
• Solid understanding of financial products, credit risk, and customer analytics.
• Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and data pipeline tools is an advantage.
• Excellent analytical, problem-solving, and communication skills.
• Ability to explain complex analytical concepts to business stakeholders clearly and effectively.
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