Jul 2019
22 Mon
23 Tue
24 Wed
25 Thu 09:15 AM – 05:45 PM IST
26 Fri 09:20 AM – 05:30 PM IST
27 Sat
28 Sun
Piyush
Developing Personalization platform for improving customer experience of millions of Indian travellers
MakeMyTrip - India’s #1 online travel platform having more than 70% of the traffic from mobile apps embarked on a journey to revolutionize its customer experience by building a scalable, personalized, machine learning based platform which powers onboarding, in-funnel and post-funnel engagement flows, such as ranking, dynamic pricing, persuasions, cross-sell and propensity models.
For a company like MakeMyTrip, the next wave of consumer growth is driven and powered by data products for personalization, context-aware mobile experiences. Having a better data architecture to ingest user activity streams (events), processing and data APIs enable a foundation for real-time feature generation for machine learning models.
Topics include:
As Technology we leverage Kafka, Spark (Streaming, SQL), Scala, Python, AWS (S3, EMR, Glue and other services), DRUID, Hive, Presto, Cassandra, RocksDB, Redis, Akka HTTP
Piyush Kumar
Head, Data Platform Engineering, MakeMyTrip
Serving as Director, Data Platform Engineering for India’s largest Online Travel Group (MakeMyTrip) with over a decade of experience in building large-scale high-performance systems and developing & architecting Data Products.
He has been part of the e-commerce Industry throughout his career in various technology leadership roles across different domains like comparison shopping, travel, marketplaces and managed teams in Website Operations, Security Operations & BigData.
In the past had co-founded startup Advisor Healthcare with a unique “Virtual Hospital” concept, based on marketplace model - where it enabled digital interactions between healthcare providers and patients.
Currently leading key strategic initiatives in data services/products for Personalization, context aware mobile experiences, Customer Segmentation and developing engagement platform over BigData systems.
https://docs.google.com/presentation/d/1MCdsekLIFO2LyXS7lgKfEqJizz1T8Nm74XKTrkR69mY/edit?usp=sharing
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