VP - Risk Analytics

About Credit Saison

Established in 2019, Credit Saison India (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. Credit Saison 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, Credit Saison India has a branch network of 80+ physical offices, 2.06 million active

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

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.

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

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

corporate venture capital, and technology.

About The Role

This critical role acts as a strategic bridge between technical modeling, cross-functional

leadership, and business execution.

In this role, you will lead and mentor a high-performing team of analysts and data scientists to

monitor portfolio behavior, track emerging delinquency patterns, and formulate data-driven credit

risk strategies. You will work in close alignment with key business stakeholders—including

Product, Engineering, Data Science, and Operations—to ensure predictive models and alternative

data streams are seamlessly deployed to drive safe, profitable asset growth across unsecured

lending portfolios.

Core Responsibilities

Team Leadership & People Management Manage & Mentor: Lead, recruit, and foster a team of risk analysts and data scientists,

driving a culture of analytical rigor, continuous learning, and innovation.

Workload & Deliverable Management: Guide the team in prioritizing analytical projects,

ensuring high-quality outputs, operational reliability, and alignment with overarching

business goals.

Stakeholder Alignment & Strategic Collaboration Cross-Functional Ownership: Act as the primary risk analytics liaison between business

heads, Product Management, Engineering, and Operations to align risk frameworks with

business margins and growth objectives.

Model & Strategy Deployment: Work side-by-side with Data Science and Tech/Product

teams to map risk strategies, policy rules, and decisioning workflows into production

environments.

Executive Reporting: Deliver clear, actionable risk intelligence and executive-level

reporting to senior leadership and committee reviews.

Portfolio Analytics & Strategy Development Granular Monitoring: Execute continuous micro-level portfolio analytics to track vintage

performance, roll-rates, and early delinquency indicators across distinct risk segments.

Lifecycle Credit Strategy: Lead the creation, evaluation, and optimization of end-to-end

credit strategies, spanning automated customer acquisition, credit limit management,

fraud containment, and automated collection triggers.

Cut-Off & Model Optimization: Collaborate with Data Science to provide domain expertise

on variable selection, score validation, and dynamic scorecard cut-off calibration for

proprietary risk models.

Data Innovation & Alternative Underwriting Data Source Expansion: Explore, evaluate, and integrate traditional (bureau) and

digital/alternative data sources to enhance model predictive power and expand credit

access.

Product Alignment: Maintain deep domain expertise in Business Loans (BL) and Personal

Loans (PL) to ensure underwriting rules adapt smoothly to evolving market conditions.

Key Requirements

Experience & Background

Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics,

Applied Mathematics, Economics, or a related quantitative field from a premier

institution.

Experience: 12+ years of progressive experience in Risk Analytics, Data Science, or

Quantitative Risk Management within Fintechs, Retail Banks, or NBFCs.

Leadership Experience: Proven track record of managing and developing small-to-mid-

sized teams of analytical professionals.

Domain Expertise: Deep functional knowledge of retail credit lines and unsecured credit

products—specifically Business Loans (BL) and Personal Loans (PL).

Technical & Functional Competencies

Programming & Querying: Advanced mastery of SQL for complex database querying and

data extraction. Strong hands-on proficiency in Python or R for statistical modeling and

data manipulation.

Statistical Rigor: Strong foundation in descriptive/inferential statistics, hypothesis

testing, experimental design, and probability distributions

Machine Learning & Modeling: Solid practical knowledge of core algorithms, including

Decision Trees, Ensemble Methods (Random Forest, XGBoost/Gradient Boosting),

Logistic Regression, and Clustering

Data Engineering & Dexterity: Demonstrated ability to clean, manipulate, and feature-

engineer large-scale structured and semi-structured datasets