Job Description

About Credit Saison

n

Established in 2019, Credit Saison India (CS India) is one of the country's fastest growing Non-

n

Bank Financial Company (NBFC) lenders, with verticals in wholesale, direct lending and tech-

n

enabled partnerships with Non-Bank Financial Companies (NBFCs) and fintechs. Its tech-enabled

n

model coupled with underwriting capability facilitates lending at scale, meeting India's huge gap

n

for credit, especially with underserved and under penetrated segments of the population.

n

Credit Saison India is committed to growing as a lender and evolving its offerings in India for the

n

long-term for MSMEs, households, individuals and more. Credit Saison India is registered with

n

the Reserve Bank of India (RBI) and has an AAA rating from CRISIL (a subsidiary of S&P; Global)

n

and CARE Ratings.

n

Currently, Credit Saison India has a branch network of 80+ physical offices, 2.06 million active

n

loans, an AUM of over US$2B and an employee base of about 1,400 employees. Credit Saison

n

India is part of Saison International, a global financial company with a mission to bring people,

n

partners and technology together, creating resilient and innovative financial solutions for positive

n

impact. Across its business arms of lending and corporate venture capital, Saison International

n

is committed to being a transformative partner in creating opportunities and enabling the dreams

n

of people.

n

Saison International is the international headquarters (IHQ) of Credit Saison Company Limited,

n

founded in 1951 and one of Japan's largest lending conglomerates with over 70 years of history

n

and listed on the Tokyo Stock Exchange. The Company has evolved from a credit-card issuer to a

n

diversified financial services provider across payments, leasing, finance, real estate and

n

entertainment. Based in Singapore, Saison International's global operations span over Singapore,

n

India, Indonesia, Thailand, Vietnam, Mexico, Brazil, with active investments in debt, equity,

n

corporate venture capital, and technology.

n

About The Role:

n

This critical role acts as a bridge between technical modeling and business execution. The

n

successful candidate will perform micro-level portfolio analysis,



track emerging delinquency

n

patterns, and formulate credit risk strategies. By partnering with Data Science, Product, and

n

Engineering teams, the role ensures that predictive risk models and alternative data streams are

n

optimally deployed to drive secure, profitable asset growth across various secured lending products.

n

Core Responsibilities:

n

• Portfolio Analytics & Delinquency Tracking: Conduct continuous, granular portfolio

n

analytics and monitor delinquency trends at a micro-level. Identify and isolate performance

n

indicators across distinct segments, to isolate risk drivers and spot growth opportunities.

n

• Lifecycle Credit Strategy Development: Lead the creation, evaluation, and refinement of

n

data-driven credit strategies across the entire customer lifecycle, including automated

n

customer acquisition, portfolio limit management, fraud containment, and automated

n

collection triggers.

n

• Trend Identification & Reporting: Uncover underlying portfolio behaviors and macro trends

n

by executing complex data cuts and rigorous statistical validation, delivering actionable

n

risk intelligence to support internal and leadership portfolio reviews.

n

• Cross-Functional Strategy Implementation: Collaborate extensively with the Product and

n

Engineering teams to map out risk strategies, policy rules, and decisioning workflows,

n

ensuring seamless implementation into the production environment.

n

• Model Optimization & Score Cut-Offs: Partner directly with the Data Science team to

n

provide crucial domain expertise on key model variables, validate predictive performance,

n

and dynamically optimize score-card cut-offs for various proprietary risk models.

n

• Data Source Evolution & Alternative Underwriting: Develop an exhaustive knowledge of

n

traditional (credit bureau)



and alternative/digital data streams. Innovate optimal

n

configurations for incorporating these diverse sources to enhance predictive accuracy.

n

• Product Architecture Alignment: Maintain a robust functional understanding of secured

n

lending products (e.g., Home Loan, LAP in both prime and affordable segment) to ensure

n

risk frameworks perfectly align with business margins and product design.

n

Key Requirements:

n

• Educational Background: Bachelor's or Master's degree in Computer Science, Engineering,

n

Statistics, Applied Mathematics, or a highly quantitative discipline from a premier institution

n

• Professional Experience: 7+ years of professional experience within Data Science, Risk

n

Analytics, or Quantitative Risk Management. Proven experience building predictive models,

n

optimizing credit policies, and delivering complex analytical insights.

n

• Technical & Tool Proficiency: Advanced mastery of SQL for complex data extraction, querying,

n

and manipulation. Strong hands-on programming proficiency in Python or R for statistical

n

analysis and machine learning.

n

• Statistical Expertise: Deep conceptual and practical understanding of advanced statistical

n

foundations, including descriptive analytics, experimental design, hypothesis testing, Bayesian

n

inference, confidence intervals, and probability distributions.

n

• Machine Learning & Data Mining: Proficiency with core machine learning techniques and

n

statistical algorithms, specifically decision tree learning, ensemble methods (Random Forest,

n

Gradient Boosting), logistic regression, and cluster analysis.

n

• Data Dexterity: Demonstrated competence in processing, clean-up, and engineering of large-

n

scale datasets, with a proven ability to work with both highly structured financial databases

n

and semi-structured/unstructured data sources.

n

• Domain Expertise: Deep functional knowledge of retail credit lines, secured credit products.

n

Exposure to Fintech lending ecosystems, retail banking, NBFC operations, or

n

SME/LAP/Secured lending is strongly preferred.

n

• Team Management: Should have managed a team directly

📌 Lead - Secured Risk (Mumbai)
🏢 Credit Saison India
📍 Mumbai