aman bajaj

• Leading the team of analysts and merchandisers to boost the traffic coming to fashion category (Apparel, Footwear and Fashion Accessories) by running multiple experiments and campaigns on Paytm and Paytm Mall app • Responsible for driving the overall grid page to product description page conversion rate by providing the consumer relevant products and best deals • To track the hourly performance of various discounted sales (Festive season, Payday, Weekend bazar, End of season, Flash Sale) and provide real time insights to category teams in order to maximize the overall revenue • Developing the overall data pipeline for the upcoming new social commerce product (Paytm Bang) to help CXOs and category teams understand the business performance

• Developed Daily/Weekly/Monthly business summary reports to enable property level performance management for United States, Canada, Brazil and Mexico region • Built multiple web scrapers to fetch property level platform and funnel metrics from Booking.com and Expedia.com to enable property level performance comparison against the competitors in the same region • Developed Organic placement Index as a metric to comprehend property rank over multiple online travel agent listings and its use to boost the ranking • Created multiple triggers/alerts at booking level to minimize revenue loss coming through low pricing of hotels • Developed Booking window/Cancellation window analysis tools to understand consumer behavior difference among different types of properties

Developed operational metrics derived from raw company data to track improvements in business efficiency in terms of student grades, program completion status, student defer/dropout rate, student feedback, in-class attendance, faculty feedback, faculty occupancy index and batch sentiment analysis • Created 100+ practice assessments for the students to emphasis more hands-on learning to get learning outcomes, developed a weekly report to track batch level adoption of the tests along with student improvement area • Defined end to end processes which resulted in: o Reducing student queries resolution time by 70% o Reducing assessment errors by 95% o Enhanced grading quality of the assessments to provide detailed feedback to the students to increase performance transparency