Data Scientist - Fraud Analytics

Key Responsibilities :

- Design and execute fraud detection models and analytics frameworks to identify suspicious activity.

- Conduct forecasting and predictive analytics to support business strategy and risk management.

- Translate complex data into strategic insights for business stakeholders.

- Work with cross-functional teams to provide actionable recommendations for credit policy, fraud prevention, and risk strategies.

- Perform data extraction, cleaning, and analysis using SQL Server and Python.

- Continuously monitor model performance and recalibrate as necessary.

- Support regulatory and compliance requirements by documenting models and methodologies.

Required Skills & Qualifications :

related field.

- 4 - 7 years of experience in credit risk modeling, fraud analytics, or predictive modeling.

- Strong proficiency in Python (data analysis, modeling libraries) and SQL Server.

- Deep knowledge of statistical modeling, forecasting, and machine learning techniques.

- Experience in developing credit scoring, PD/LGD/EAD, or fraud detection models.

- Excellent problem-solving and analytical skills with attention to detail.

- Strong communication and presentation skills for stakeholder management.