Digitizing and improving Sales, Operations, Academics, Marketing through analytics

Teach and mentor students and working professionals in the concepts of Machine Learning which includes:1. Statistics: Training in Statistics module.2. Python: Training in Python module.3. Machine Learning algorithms: Training in ML and. DL (Deep Learning) concepts.

1. Credit Risk Strategy – developed strategy for credit limit management and credit limit assignment for banking client in Egypt2. Data Strategy for Mastercard Investments – developed an algorithm to validate the quality of SME data provided by vendors for synergy with Mastercard data3. Go-to-market strategy – performed spend analysis, customer profiling, and geographical analysis to develop strategy for introducing Apple-pay for a leading bank in Switzerland4. Digital Acquisition and Audience Expansion (MS) – managed services project for card issuer in Thailand5. Cross Border Travel PO – delivered audience profiles and behavioral metrics for cross-border customers of banking client in France6. Fraud rules for Consumer and Commercial porfolios of a leading bank in Latin America

- Customer Service Routing Risk Strategy based on NLP : Amazon.com- Customer segmentation and Ideal Customer profile using VoC (Voice of Customer) : Segment.io- Total Cost-to-Serve integrated solution and dashboard to manage restaurant operations and finances : Panera Bread- Revenue and Finance optimization : Pfizer- Organizational restructuring and Performance Management strategy : Pfizer

- Developed a Seller Rating system. This is being used to measure and set performance targets for all merchants on Paytm. It is also being used to penalize and delist those merchants who do not meet the same.- Developed a universal Customer Targetting System using Machine Learning (Decision Trees). It is a system which can predict customer behaviour and provide sets of target audiences for specific campaigns to promote cross-sell and up-sell activity.- Built and operationalized the customer fraud detection engine to stop reselling activity with an accuracy of 85%.- Built and operationalized the merchant fraud detection engine to check merchant-customer collusion with an accuracy of 95%.

- Used Machine-Learning(Logistic Regression) and statistics to predict customer risk score and customer trust score.- Set up user-engagement campaigns in recharge business (Prepaid, postpaid) using Linear Regression and predictive data modeling.- Set up a customer triangulation system using various data points from the transactional and interactional history of customers.- Maintained custom databases and flat-tables, integrating data from multiple sources.- Set up automated cronjobs, MIS reports, and personnel-performance reports.- Fulfilled ad-hoc data requirements.