Data Scientist

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.

• 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.

• Excellent analytical, problem-solving, and communication skills.

• Ability to explain complex analytical concepts to business stakeholders clearly and effectively