Aug 2022 – Jan 2025 · 2 yrs 5 mos · Bangalore Urban, Karnataka, India

• Engineering AI Driven Sales

Mar 2021 – Apr 2022 · 1 yr 1 mo · Bangalore Urban, Karnataka, India

• Contributed towards building products for cloud security at OCI

May 2018 – Mar 2021 · 2 yrs 10 mos · Bangaon Area, India

• Worked as Lead developer on Automation Project for Flipkart. Owned end to end from solutioning till rollout of project.
• https://www.businessinsider.in/flipkart-announces-delivery-robots-automation/articleshow/68493938.cms

Apr 2017 – Apr 2018 · 1 yr · Bengaluru Area, India

• At pipecandy, I am responsible for handling data at scale and making it available for application/analytics team. I am majorly using tools like Elasticsearch, Spark, SQS, S3 and Python language to achieve this. Other than performing ETL processes, I also have ownership of a on demand ML platform which can be used by our customer and internal teams for running models on selected data points.

Aug 2015 – Mar 2017 · 1 yr 7 mos · Gurgaon, India

• Responsible for building the advertisement service exclusive for Snapdeal sellers.
• 1. Generating Feeds for Dynamic Ads based on Users history on Snapdeal platform
• 2. Related Ads based on the Product Page on which user is browsing
• 3. Building a DMP (Data Management Platform) which can profile users based on their actions and interests. A platform that sellers can use to target a specific group of users
• 4. Working on an Ad Serving Platform which can serve ads in two ways (a) To Websites associated with Snapdeal (b) Via Real Time Bidding.
• 5. Building a system to monitor the highly concurrent system for health, response time and possible issues.
• 6. Ensuring consistency of data being produced by multiple sources and distribute it to multiple consumers.
• Technologies: Kafka, Cassandra, Guava Cache, CQEngine, RocksDB, Codahale metrics, Amazon S3
• Language: Java, Platform: Linux

May 2015 – Aug 2015 · 3 mos · Chennai Area, India

• Responsibilities associated with my job
• Building a better data collection strategy for the DSP server
• Building data models and implementations to meet specific campaign goals such as ROAS, CTR, CPC, CPD and CPA.
• Implementation of multi-variate decisioning system and a rule based system to drive better campaign performance
• Designing, planning and implementation of a Lambda architecture for Reduce Data to drive efficient real-time data for campaign performance
• Assist campaign operations through automated daily / weekly / monthly reports
• Identification of data patterns that could be used to improve targeting and relevance.
• Implementation of improved data collection of user profile information to drive better results through an in house Data management Platform
• Ensuring Improved bidder bid price predictions.
• Implementation of rule based system together with the machine learning system to provide more control to advertisers
• Key technologies - Java / Hbase / Cassandra
• Key algorithms - Weka forecaster, Logistic regression, Random forest.