Nov 2019 – Jul 2021 · 1 yr 8 mos · Bengaluru, Karnataka, India

• As a distinguished team lead, led the team to provide useful insights in various fields including recommendation engine, customer acquisition, retention and trending hashtag

Jul 2018 – Oct 2019 · 1 yr 3 mos · Gurgaon, India

• User acquisition : Scaled DAU form 50 K to 2.5 M by optimizing marketing channels based on an app install to LTV analytics framework in addition to leading the digital marketing team
• Designed an automated anomaly detection system to send alert if there are unexpected
• changes in recommendations and coin allotment and redemption
• Designed, executed and analyzed multiple A/B experiments in order to improve recommendation engine and user engagement on the platform
• Evaluated performance metrics to identify key areas for growth and worked across teams to get the solutions implemented

Mar 2016 – Jun 2018 · 2 yrs 3 mos · New Delhi Area, India

• Using machine learning to drive data- based decision making for e-commerce companies in India. These solutions enhance existing marketing and growth efforts for these companies. Additionally, we prepared competitive industry landscapes for investors in the space.
• Clients : Emerging and entrant startups, existing e-commerce companies
• Methodology : Deployed Data Mining models to estimate companies' different growth related metrics.
• 1. Developed a scalable, unsupervised learning k-means collaboration model using user's behaviour. Feature engineering was executed to come up to optimised user's behaviour like smoothening the behaviour.
• 2. Designed and developed NLP deep learning model to classify billions of text rows to certain defined categories and extract valuable information from them.

Jun 2013 – Mar 2016 · 2 yrs 9 mos · Noida Area, India

• Collections : Managed delinquent customers portfolio. Built predictive model to offer settlements to delinquent customers based on their propensity to pay of their loan. Managed relations with debt collection agencies and sale of bad loans.
• Risk analytics : Generated monthly risk reports in addition to managing volumes and bad rates of various segments using champion-challenger approach.
• Built various ensemble models like random forest and gradient boosting in addition to basic linear regression and naive bayes models to manage risk of the lending portfolio.