Senior Data Analyst

Ganit Business Solutions; Mumbai; On-site; INR 900,000 - 1,800,000; Full time

Job summary

Ganit Business Solutions in Mumbai seeks a Senior Data Analyst/Data Scientist with 3–5 years of credit risk modelling and risk analytics. You will work with risk datasets to develop data-driven insights and predictive models for credit risk assessment and business decisions.

Key responsibilities include analyzing large datasets, developing and validating PD/LGD/EAD models, performing risk analytics and portfolio analysis, and building dashboards.

Qualifications

• 3–5 years of relevant experience in Data Analytics, Data Science, Credit Risk, or Risk Analytics.
• Hands-on experience in credit risk modelling and credit risk analytics.
• Strong proficiency in Python and SQL.
• Experience with statistical analysis, predictive modelling, and machine learning techniques.

Responsibilities

• Analyze large datasets to identify trends, patterns, and insights related to credit risk and portfolio performance.
• Develop, validate, and monitor credit risk models for risk assessment and prediction.
• Work on credit risk modelling techniques, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Perform risk analytics, portfolio analysis, customer segmentation, and creditworthiness assessment.
• Build and evaluate statistical and machine learning models to support credit risk management.
• Conduct data cleaning, feature engineering, exploratory data analysis, and model performance evaluation.
• Collaborate with business, risk management, and technical teams to translate business requirements into analytical solutions.
• Prepare reports, dashboards, and presentations to communicate insights and model outcomes to stakeholders.
• Monitor model performance and identify opportunities to improve model accuracy and risk assessment processes.

Skills

Python

SQL

Statistical analysis

Machine learning

Data visualization

Credit risk concepts

Problem solving

Communication

Tools

Power BI

Tableau

Job description

Experience: 35 Years
Location: [Mention Location]
Employment Type: Full-time

Role Overview

We are looking for a skilled Senior Data Analyst / Data Scientist with 3–5 years of experience in Credit Risk, Credit Risk Modelling, and Risk Analytics. The ideal candidate should have strong analytical and problem-solving skills, experience working with risk-related datasets, and the ability to develop data-driven insights and models to support credit risk assessment and business decision-making.

Key Responsibilities

• Analyze large datasets to identify trends, patterns, and insights related to credit risk and portfolio performance.
• Develop, validate, and monitor credit risk models for risk assessment and prediction.
• Work on credit risk modelling techniques, including Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD), wherever applicable.
• Perform risk analytics, portfolio analysis, customer segmentation, and creditworthiness assessment.
• Build and evaluate statistical and machine learning models to support credit risk management.
• Conduct data cleaning, feature engineering, exploratory data analysis, and model performance evaluation.
• Collaborate with business, risk management, and technical teams to translate business requirements into analytical solutions.
• Prepare reports, dashboards, and presentations to communicate insights and model outcomes to stakeholders.
• Monitor model performance and identify opportunities to improve model accuracy and risk assessment processes.

Required Skills and Qualifications

• 3–5 years of relevant experience in Data Analytics, Data Science, Credit Risk, or Risk Analytics.
• Hands-on experience in credit risk modelling and credit risk analytics.
• Strong proficiency in Python and SQL.
• Experience with statistical analysis, predictive modelling, and machine learning techniques.
• Understanding of credit risk concepts, risk scoring, credit underwriting, and portfolio risk assessment.
• Experience with data visualization tools such as Power BI or Tableau is an advantage.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience in banking, financial services, fintech, or lending domains.
• Knowledge of credit scoring models, Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).
• Familiarity with model validation, model monitoring, and regulatory risk frameworks.
• Experience working with large datasets and translating analytical findings into actionable business insights.