Posted:2 months ago| Platform:
Work from Office
Full Time
Job Purpose "This position is open with Bajaj Finance ltd." Duties and Responsibilities ƒ˜Provide analytical solutions through statistical modeling, credit policy and strategy, reporting and data analysis for the BFL businesses ƒ˜Monitor, maintain and improve all scorecards, policies and processes across portfolios and ensure its effectiveness ƒ˜Support any adhoc deep dive data analysis on portfolio matrices ƒ˜Track and improve key performance indicators, losses and portfolio quality. Provide deep dive analysis on portfolio matrices. ƒ˜Building of ML based models to achieve maximum match and catch rate. ƒ˜Building of ML based capabilities across the organization as on when required. ƒ˜Work closely with business team to understand their need and provide Analytical solution. ƒ˜Assess if any early warning signals using data analysis and segmentations and take pro-active policy actions as and when required ƒ˜Support in managing and improving various offer strategies, control offer generation and distribution through data analysis ƒ˜Work closely with Product, Sales and Risk teams to support business growth and drive new initiatives ƒ˜Ongoing liaising with IT, Credit and BIU teams to ensure all policies, processes, data flow are working efficiently and all required changes are build and implemented suitably Required Qualifications and Experience ƒ˜Relevant analytical experience in Scorecard development, ML modelling, Segmentation and Clustering. ƒ˜Preferred languages:SAS, SQL, R/Python. ƒ˜Classical stat techniques:Regression, Logistic regression, Clustering, Dimensionality reduction techniques, Hypothesis testing. ƒ˜ML algo:KNN, NBM, DT, CART, Boosting & Bagging models, SVM, Neural net, Ensemble models etc. ƒ˜Experience in handling huge data base and the ability to do root cause analysis. ƒ˜Individual contributor with the capability to deliver projects within timeline ƒ˜Effective verbal and written communication skills. ƒ˜MBA / Post Graduate with 2-4 years experience in financial services
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