Lendingkart - Vice President - Credit Data Science

Job Description :

(1) Deep of credit bureau variables and set up pipes and processes to capture the credit variables in the database.

(2) Ability to explore alternate sources of data for underwriting.

(3) Extremely comfortable with bureau variables and should have some experience working with bureau.

(4) Good understanding of credit models, default prediction models, propensity models and collections models, fraud models, customer segmentation, survival models.

(5) Ability to simplify difficult concepts into English.

(6) Experience working in credit modeling divisions of Capital one, HSBC, Equifax, Cibil, Experian, American Express.

Desired Candidate Profile :

1) Action bias : believes in getting to a feasible solution first rather looking for the optimal solution.

(2) Strong aptitude for creating mathematical models from scratch, creativity.

(3) Thorough understanding of KS, Ginnie, default curves, loss curves, WOE, IV etc.

(4) Thorough in logistic regression, random forest, SVM, decision trees, clustering models.

(5) Creativity to overcome large as well as small data issues.

(6) High degree of creativity and tenacity to get model into production.

(7) Ability to explain concepts in English - strong presentation skills.

(8) Hands on person in python, R,SQL.

(9) Machine learning, linux.

(10) Familairy with AWS, kafka, redshift.