About me

I’m a business analytics professional with 3+ years of experience in data mining techniques, predictive modeling, and campaign management in the consumer and commercial lending industries in the United States. I’ve worked extensively on projects related to Credit Risk and Marketing Management spanning the entire Customer Life Cycle - Acquisition, Retention, Collections/Recovery, and Operations.

Academic Background

Professional Background

Barri Financial Group July 2020 – June 2022

Associate Data Scientist

  • Created a logistic regression model in Python with Statsmodel to assess the likelihood of an active customer closing (paying off) their active loan. The model was then utilized to create a collection strategy, which resulted in a 21% increase in collection rate.

  • Conducted performance analysis of the high-value loan product to check its feasibility under the volatile circumstances of the pandemic and used the results to drive business decisions.

  • Analyzed customer movement between different past-due delinquency buckets, segmented by store-wise active ledger, with the goal of improving employee-incentive policy and aligning it with business needs.

  • Conducted data analysis for the optimization of resource requirements at stores based on number of transactions and the average time needed for each transaction to then create a usable, regularly updated data model for managers, helping them optimize the FTE requirements, delivering projected savings of $3M a year across stores.

Modelytics India Pvt. Ltd. February 2019 – June 2020

Business Analyst

  • Developed and implemented several real-time and recurring dashboards for KPIs such as portfolio risk exposure, the performance of marketing campaigns and CSR operation performance for a financial services company in the US.

  • Worked on multiple bi-annual Direct Marketing (DM) Campaigns, which required working with credit bureau information to process and create targetable lists of prospective customers, as part of enhancing the unsecured loan portfolio in a manner aligned with the company’s goals.

  • Worked on calculating the economic value of DM customers to ascertain the impact of campaigns and create a sound basis for volume control and risk reduction for future campaigns, based on the results. This helped reduce the target volume by 19.2%, while still increasing responses.

  • Created predictors and the developed a PD model to assess the risk of borrowers making use of their transaction history with the company, using SQL for data extraction and Python for data manipulation.

Experience with R

I’ve had no experience with R so far. As a proficient Python user, I’m finding some similarities between the two, which is helping me get up to speed a bit quicker.

Experience with other analytics software

As an analyst, I’ve had the opportunity to work extensively with a few tools, some of them being Python, Excel, and QlikView.