Ujjwal Sridhar Lingam

Experience

• 

  Mu Sigma Inc.

  May 2015 - Jan 2017

  Trainee Decision Scientist

  - US Compliance and Ethics Engagement for a Globally Leading Retail Client1. Led a team of four that assists clients on developing Tableau dashboards for more than 4500+ stakeholders resulting in money saved in fines more than 450K this year (Data Visualization and Data Manipulation)- Marketing Finance and Strategy Engagement for a Globally Leading Retail Client1. Evaluated marketing campaign effectiveness, using customer behavior matching (Propensity Modelling). Received spot award for flawless delivery, while reducing turnaround time, of the pre-existing report from 4 days to 3 hours (Query Optimization and Machine Learning)2. Led a team of three to evaluate the drivers of sales of newly opened store, consequently helping client’s real estate team plan consecutive budgets better by using stacked ensemble models (Prescriptive Analytics and Machine Learning) 3. Designed and developed web based tool in R Shiny to perform competitive analysis to understand key competitors and items causing lost sales (Dashboard Design) Show less

• 

  Amazon

  Feb 2017 - now

  - Insights and Statistical Analysis Team, Amazon India Payments Pvt. Ltd.1. N2EPS (New to External Payments Service) lookalike models tested to provide +2x purchase conversion of customers. This propensity model identified the 10% base of potential new customers with high propensity (>0.50) to do their first prepaid transaction and which observed 2x increase in purchase conversion in the pilot experiment on a major third party food delivery applicationFurther applications: 1.A. The marketing team drove higher ROI from onsite gateway bunk SOV (Share of voice or marketing asset bandwidth ) allocation by specifically targeting the high-propensity base and spreading the SOV throughout the month versus spreading SOV thin across the entire N2EPS base1.B. Extending the model to other use cases (Marketing Customer Segmentation and Targeting)2. Owned data/compute infrastructure initiatives for the team and developed Amazon Pay Feature Repository of about 200+ variables saving ~400-man hours for model/dashboard building exercises for the internal and three external teams (India ML, Category and Reverse Logistics) Show less - Defined & developed driver model to identify key levers driving program prioritisation across electronification team resulting in incremental 141 basis points impact (Regularised Models and Principal Component Analysis)- Built deep dive dashboard that serves as a self-serve tool for Payments Product team that answers ~80% of ad-hoc asks, saving ~8 man hrs./wk. in Tableau- Designed and developed Datamart for customer payments by aggregating data across 7 different data streams into one unified dataset now being used by Reverse Logistics, Core Machine Learning Teams and other teams (Working with multiple ambiguous sources of data)- Qualified all the three modules (MATH, DATA, and REGR) of Foundational track for Amazon’s Machine Learning University Show less

  • Senior Product Manager Tech

    Jan 2025 - now

  • Senior Product Manager

    Oct 2022 - Jan 2025

  • Senior Product Manager

    May 2022 - Nov 2022

  • Senior Business Intelligence Engineer (BIE - III)

    Oct 2021 - Apr 2022

  • Business Intelligence Engineer II

    May 2020 - Oct 2021

  • Business Intelligence Engineer - II

    Jan 2020 - Apr 2020

  • Senior Business Analyst

    Oct 2018 - Jan 2020

  • Business Analyst

    Feb 2017 - Sept 2018