Credit Saison - Risk Analyst

About Credit Saison :

A Neo-Lending Conglomerate here to enable India's credit growth story, Credit Saison India, emboldened by our Global MNC parent, is here to accelerate India's credit growth story: by building a Technology-Led Neo-Lending Conglomerate. Across our verticals, we offer bespoke solutions to meet the various credit needs of Individuals, SMEs, FinTech's, and NBFCs. Credit Saison India ("CS India"), having been founded in 2018, operates under the registered name Kisetsu Saison Finance India Private Limited as an MNC subsidiary of its parent company - Credit SaisonCo. Ltd in Japan. Across our various business verticals like

Wholesale Financing, Co-origination Financing, Consumer Financing, and SME Financing we look towards reaching resilient Assets Under Management ("AUM") of US1bn in record time.

More about us on https://www.creditsaison.in

Key Responsibilities :

- Collaborate and coordinate across functions to dissect business, product, growth, acquisition, retention, and operational metrics.

- Execute deep & complex quantitative analyses that translate data into actionable insights

- Should have a good understanding of various unsecured credit products

- The ability to clearly and effectively articulate and communicate the results of complex analyses

- Create a deep-level understanding of the various data sources (Traditional as well as alternative) and optimum use of the same in underwriting.

- Work with the Data Science team to effectively provide inputs on the key model variables and optimize the cut-off for various risk models

- Helps to develop credit strategies/monitoring framework across the customer lifecycle (acquisitions, management, fraud, collections, etc.)

- Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identification of segments, programs, locations, and profiles that are delinquent or working well.

Basic Qualifications :

- Bachelors or Master's degree in, Statistics, Economics, Computer Science, or other Engineering disciplines.

- 2-5 years of experience working in Data science/Risk Analytics/Risk Management with experience in building models/Risk strategies or generating risk insights

- Proficiency in SQL and other analytical tools/scripting languages such as Python or R is a must

- Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions

- Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.

Good to have :

- Exposure to the Fintech industry, preferably digital lending background

- Exposure to visualization techniques & tools