Key Responsibilities :

- Develop and implement credit risk models to assess borrower risk and optimize portfolio performance.
- 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 :





- Bachelors/Masters degree in Statistics, Mathematics, Economics, Computer Science, or related field.
- 4 - 7 years of experience in credit risk modeling, fraud analytics, or predictive modeling.
- Robust 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.

📌 Data Scientist - Fraud Analytics (India)
🏢 Skyleaf Consultants
📍 India