This role is for one of the Weekday's clients

Salary range: Rs 1000000 - Rs 3500000 (ie INR 10-35 LPA)

Min Experience: 1 years

Location: Bengaluru

JobType: full-time

We are seeking a Credit Risk Analyst with strong Python and SQL skills to join our risk management team. In this role, you will analyze financial data, assess credit risks, and develop models that help optimize credit decisions. You will work closely with cross-functional teams, including finance, data science, and product, to ensure robust risk assessment strategies.

This is an excellent opportunity for a data-driven professional looking to make an impact in the credit risk space while working in a dynamic and fast-paced environment.

Key Responsibilities:

•  Risk Analysis & Modeling: Analyze customer creditworthiness using data-driven techniques and develop models to predict default risk and optimize lending decisions.
•  Data Extraction & Processing: Use SQL to extract and manipulate large datasets from multiple sources to support risk analysis and reporting.
•  Machine Learning & Predictive Modeling: Leverage Python to build and improve risk models, including credit scoring, fraud detection, and loss forecasting.
•  Portfolio Monitoring: Continuously monitor credit risk metrics and portfolio performance, identifying trends and recommending strategic adjustments.
•  Regulatory Compliance: Ensure credit risk assessments align with regulatory requirements and internal risk policies.
•  Reporting & Visualization: Create dashboards and reports that provide insights into credit risk trends and performance for stakeholders.
•  Collaboration: Work closely with data science, finance, and product teams to refine credit strategies and improve decision-making processes.

Required Skills & Qualifications:

•  1+ years of experience in a credit risk, data analytics, or financial modeling role. 
• Strong proficiency in Python for data analysis, statistical modeling, and machine learning applications.
• Advanced SQL skills to query and process large datasets efficiently.
• Experience with credit risk modeling techniques, probability of default (PD), loss given default (LGD), and expected loss (EL) models is a plus.
• Familiarity with financial statements, lending processes, and credit bureau data.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to communicate technical concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience in banking, fintech, or financial services.
• Knowledge of risk frameworks such as Basel II/III, IFRS 9, or CECL.
• Familiarity with data visualization tools (e.g., Tableau, Power BI) for reporting.
• Understanding of cloud platforms like AWS, GCP, or Azure for data processing.