Sr. Analyst/ Lead- Quantitative Credit Risk

About Us:

Solytics Partners is a Global Analytics firm, recognized with multiple industry awards for innovation and excellence. Our team comprises experts with deep domain knowledge in risk, analytics, AI/ML, AML/FCC, and fraud. By converging this expertise with cutting-edge technologies like AI, Machine Learning, Generative AI, and Large Language Models (LLMs), we deliver powerful automated platforms and incisive point solutions.

Our offerings enable clients to streamline and future-proof their risk, AML, and analytics processes, comply seamlessly with global regulations, and safeguard financial systems. Whether it's solving complex challenges or driving operational efficiency, Solytics Partners is committed to empowering organizations with transformative tools to stay ahead in an evolving regulatory landscape.

Job Summary:

We are looking for a skilled Credit Risk Modelling professional to join our risk analytics team. The role involves development, validation, and enhancement of a wide range of credit risk models, including regulatory, internal, and scorecard-based models, along with integration of AI/ML techniques within the credit risk framework. This is a dynamic role offering exposure across portfolios, methodologies, and model types rather than being limited to a specific model.

Key Responsibilities:

• Develop, enhance, and maintain credit risk models across portfolios (Retail / Wholesale).
• Work on a variety of model types including:
• Regulatory models (PD, LGD, EAD, IFRS9, Basel)
• Internal risk models
• Application / behavioral scorecards
• Apply statistical and machine learning techniques to improve model performance and predictive power.
• Perform data analysis, feature engineering, and model calibration.
• Conduct model validation, backtesting, and performance monitoring.
• Ensure models comply with regulatory requirements and internal governance standards.
• Collaborate with stakeholders across Risk, Business, and Technology teams.
• Prepare model documentation and support audit/regulatory reviews.

Key Requirements:

• 3+ years of experience in credit risk modelling or risk analytics.
• Strong understanding of credit risk concepts and model lifecycle.
• Experience working on one or more:
• PD / LGD / EAD models
• IFRS9 models
• Scorecards (application / behavioral)
• Hands-on experience with statistical and machine learning techniques (e.g., regression, decision trees, random forests, boosting, etc.).
• Proficiency in tools such as Python / R / SAS / SQL.
• Strong data handling and analytical skills.
• Good understanding of model validation techniques and performance metrics (KS, Gini, ROC, etc.).
• Familiarity with regulatory frameworks (Basel, IFRS9) is a plus.
• Strong problem-solving and communication skills.