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Urgent! Credit Saison - Risk Analyst - SQL/R/Python Job Opening In Bengaluru – Now Hiring KISETSU SAISON FINANCE (INDIA) PRIVATE LIMITED

Credit Saison Risk Analyst SQL/R/Python



Job description

<p>Key Responsibilities :<br/><br/> - Collaborate and coordinate across functions to dissect business, product, growth, acquisition, retention, and operational metrics.

<br/><br/>- Execute deep & complex quantitative analyses that translate data into actionable insights <br/><br/>- Should have a good understanding of various unsecured credit products <br/><br/>- The ability to clearly and effectively articulate and communicate the results of complex analyses <br/><br/>- Create a deep-level understanding of the various data sources (Traditional as well as alternative) and optimum use of the same in underwriting.

<br/><br/>- Work with the Data Science team to effectively provide inputs on the key model variables and optimize the cut-off for various risk models <br/><br/>- Helps to develop credit strategies/monitoring framework across the customer lifecycle (acquisitions, management, fraud, collections, etc.) <br/><br/>- Conduct Portfolio Analysis and Monitor Portfolio delinquencies at a micro level, identification of segments, programs, locations, and profiles that are delinquent or working well.

<br/><br/>Basic Qualifications : <br/><br/>- Bachelors or Master's degree in, Statistics, Economics, Computer Science, or other Engineering disciplines.

<br/><br/>- 2+ years of experience working in Data science/Risk Analytics/Risk Management with experience in building models/Risk strategies or generating risk insights <br/><br/>- Proficiency in SQL and other analytical tools/scripting languages such as Python or R is a must<br/><br/>- Deep understanding of statistical concepts including descriptive analysis, experimental design and measurement, Bayesian statistics, confidence intervals, Probability distributions<br/><br/>- Experience and knowledge of statistical modeling techniques: GLM multiple regression, logistic regression, log-linear regression, variable selection, etc.<br/><br/> Good to have: <br/><br/>- Exposure to the Fintech industry, preferably digital lending background <br/><br/>- Exposure to visualization techniques & tools</p> (ref:hirist.tech)


Required Skill Profession

Mathematical Science Occupations



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