AVP - Consumer Risk

Credit Saison India; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Credit Saison India is seeking a skilled data science professional to enhance risk analytics across its lending portfolio. You will analyze delinquencies, develop credit strategies across the customer lifecycle, and identify portfolio trends to improve risk controls.

The role requires strong SQL and Python/R proficiency, experience with fintech lending, and the ability to translate data insights into actionable risk models and underwriting improvements.

Qualifications

• Bachelors or Master's degree in Statistics, Economics, Computer Science, or other Engineering disciplines.
• 5-10 years of experience in Data science/Risk Analytics/Risk Management with experience in building models or risk strategies.
• Proficiency in SQL and scripting languages such as Python or R; strong statistical concepts and data mining techniques.
• Fintech/Retail lending experience is preferred.

Responsibilities

• Conduct Portfolio Analysis and monitor delinquencies at a micro level.
• Help develop credit strategies across the customer lifecycle (acquisitions, management, fraud, collections).
• Identify trends by performing analytics at various cuts for the Portfolio.
• Provide analytical support to internal reviews of the portfolio and identify opportunities to improve quality.
• Work with Product and Engineering teams to implement risk strategies and optimize model variables.
• Understand data sources (traditional and alternate) and apply them to underwriting, including unsecured credit products.

Skills

SQL

Python

R

Statistics

Machine Learning

Risk Analytics

Education

Bachelor's/Master's in Statistics, Economics, Computer Science, or Engineering

Job description

About Credit Saison India

Established in 2019, CS India is one of the country’s fastest growing Non-Bank Financial Company (NBFC) lenders, with verticals in wholesale, direct lending and tech-enabled partnerships with Non-Bank Financial Companies (NBFCs) and fintechs. Its tech-enabled model coupled with underwriting capability facilitates lending at scale, meeting India’s huge gap for credit, especially with underserved and under penetrated segments of the population.

Credit Saison India is committed to growing as a lender and evolving its offerings in India for the long-term for MSMEs, households, individuals and more. CS India is registered with the Reserve Bank of India (RBI) and has an AAA rating from CRISIL (a subsidiary of S&P Global) and CARE Ratings.

Currently, CS India has a branch network of 45 physical offices, 1.2 million active loans, an AUM of over US$1.5B and an employee base of about 1,000 people.

Credit Saison India (CS India) is part of Saison International, a global financial company with a mission to bring people, partners and technology together, creating resilient and innovative financial solutions for positive impact.

Across its business arms of lending and corporate venture capital, Saison International is committed to being a transformative partner in creating opportunities and enabling the dreams of people.

Based in Singapore, over 1,000 employees work across Saison’s global operations spanning Singapore, India, Indonesia, Thailand, Vietnam, Mexico, Brazil.

Saison International is the international headquarters (IHQ) of Credit Saison Company Limited, founded in 1951 and one of Japan’s largest lending conglomerates with over 70 years of history and listed on the Tokyo Stock Exchange. The Company has evolved from a credit-card issuer to a diversified financial services provider across payments, leasing, finance, real estate and entertainment.

• Bachelors or Master's degree in, Statistics, Economics, Computer Science, or other Engineering disciplines
• 5-10 years of experience working in Data science/Risk Analytics/Risk Management with experience in building the models/Risk strategies or generating risk insights
• Proficiency in SQL and other analytical tools/scripting languages such as Python or R- Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions- Proficiency with statistical and data mining techniques
• Proficiency with machine learning techniques such as decision tree learning etc.- Should have an experience working with both structured and unstructured data- Fintech/Retail lending experience is preferred

About Credit Saison India

Established in 2019, CS India is one of the country’s fastest growing Non-Bank Financial Company (NBFC) lenders, with verticals in wholesale, direct lending and tech-enabled partnerships with Non-Bank Financial Companies (NBFCs) and fintechs. Its tech-enabled model coupled with underwriting capability facilitates lending at scale, meeting India’s huge gap for credit, especially with underserved and under penetrated segments of the population.

Credit Saison India is committed to growing as a lender and evolving its offerings in India for the long-term for MSMEs, households, individuals and more. CS India is registered with the Reserve Bank of India (RBI) and has an AAA rating from CRISIL (a subsidiary of S&P Global) and CARE Ratings.

Currently, CS India has a branch network of 45 physical offices, 1.2 million active loans, an AUM of over US$1.5B and an employee base of about 1,000 people.

Credit Saison India (CS India) is part of Saison International, a global financial company with a mission to bring people, partners and technology together, creating resilient and innovative financial solutions for positive impact.

Across its business arms of lending and corporate venture capital, Saison International is committed to being a transformative partner in creating opportunities and enabling the dreams of people.

Based in Singapore, over 1,000 employees work across Saison’s global operations spanning Singapore, India, Indonesia, Thailand, Vietnam, Mexico, Brazil.

Saison International is the international headquarters (IHQ) of Credit Saison Company Limited, founded in 1951 and one of Japan’s largest lending conglomerates with over 70 years of history and listed on the Tokyo Stock Exchange. The Company has evolved from a credit-card issuer to a diversified financial services provider across payments, leasing, finance, real estate and entertainment.

Basic Qualifications

• Bachelors or Master's degree in, Statistics, Economics, Computer Science, or other Engineering disciplines
• 5-10 years of experience working in Data science/Risk Analytics/Risk Management with experience in building the models/Risk strategies or generating risk insights
• Proficiency in SQL and other analytical tools/scripting languages such as Python or R- Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions- Proficiency with statistical and data mining techniques
• Proficiency with machine learning techniques such as decision tree learning etc.- Should have an experience working with both structured and unstructured data- Fintech/Retail lending experience is preferred

Key Responsibilities

• Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identification of segments, programs, locations, and profiles which are delinquent or working well.
• Helps to develop credit strategies across the customer lifecycle (acquisitions, management, fraud, collections, etc.)
• Identify trends by performing necessary analytics at various cuts for the Portfolio
• Provide analytical support to various internal reviews of the portfolio and help identify the opportunity to further increase the quality of the portfoli
• Work with Product team and engineering team to help implements the Risk strategies- Work with Data science team to effectively provide inputs on the key model variables and optimize the cut off for various risk models
• Create a deep level understanding of the various data sources (Traditional as well as alternate) and optimum use of the same in underwriting- Should have good understanding about various unsecured credit products- Should be able to understand the business problems and helps convert them into the analytical solutions