> Designed and developed Meta Shops product promotions infrastructure as a feature across FB and IG platforms. Served as the team lead on design and implementation of seller facing promotion creation tools which includes fixed amount off, percentage off, minimum subtotal, minimum quantity, tiered, free shipping, bxgy discount types.

> Worked with XFN partners (PM, PMM, Designers, Researchers and Data Scientists) to devise the GTM strategy, determine the product goal, success and launch metrics. Rolled out the product to the alpha sellers control group; collected and incorporated feedback and then gradually released to the public. Created extensive dashboards using unidash with scuba queries and dia-query to view discount creation and usage metrics.

> Built internal curation tools to facilitate better curated collection creation process with the focus on product promotions, holiday sales events, trending products and sellers’ diversity profile. Created wireframes with user flows and built the mvp to get the leaders' buy-in.

> Worked on facilitating discount tiles as a feature on shops' storefront. Built discount features into an open source shops implementation using Facebook Graph APIs to make it easy for partners to AB test/experiment shops features.

> Owned end-to-end design and delivery of a benefit-based feature Free Shipping on Subsequent Orders. Led a team of 5 engineers & worked with 8 cross functional teams during the implementation phase providing design and code reviews, hardware scaling, creating metrics, monitors and dashboards along with go-to-market strategy. Order volume doubled the daily pattern for the customer cohort.

> Designed and developed a product that allows customers to Buy More & Save More. Owned end-to-end customer order checkout experience including applying the promotion. Programmed UX components from wireframes in an extensible fashion reducing developers time by 50%. Poised to generate 0.01% increase in revenue to Amazon by end of 2020

> Oversaw Buy More Save More feature extension onto a new page to completion, designed a working solution, created a launch plan, allocated appropriate engineer bandwidth, mentored engineers and released it to the market on time

> Orchestrated business metrics meetings, analyzed business metrics to verify areas of strengths and weaknesses. Found and avoided potential concern which could have caused losing 99% of project Capex

> Executed sprint planning meetings as a scrum master, managed story intakes and backlogs, created processes to keep sprint velocity in check

> Proposed PR/FAQ for increasing Buy More Save More sales with cost spending-saving analysis. Influenced product decisions by analyzing A/B testing and customer behavior metrics.

> Developed an Android and iOS application feature which infuses location awareness into Amazon pages giving a better selection of products and experience to customers. Increased the app load only by 1.5% to effectively work well on low latency devices and marketplaces. Reduced customer frustration of product unavailability to less than 3%

> Organizer: Organization level hackathon, team building activities. Volunteer: New Hire Orientation Ambassador, Amazon wide community engagement events.

> Predict the request execution time and an optimal scaling factor to balance the server load for a cloud supply chain platform using Machine Learning and Data modeling algorithms

> Fitted DecisionTree, SGD and RandomForest regression models at multiple levels to train the dataset and make accurate predictions

> Designed architecture and logic flow diagrams and implemented the model builder and request meter predictor business logic

> Designed assignments, assisted and graded student projects and worked closely with the professor for CS-GY 9223 Cloud Computing and Big Data Analytics course

Course Overview:

A graduate level course on Cloud Computing and Big Data with emphasis on hands-on design and implementations. In addition to Infrastructure as a Service (IaaS) and Platform as a Service (PaaS) cloud technologies and concepts, Big Data technologies and platforms (Hadoop ecosystem) is also covered. By the end of the course, every student will have fair amount of knowledge about how to use a Cloud, write applications on Cloud and build your own private Cloud as well as manage and build applications on Big Data platform.