• Spearheaded the team that built a machine learning system which provides recommendations and suggestions to ~30 million users, trained on the harvested Q/A repository from different consumer products.• Designed and launched a self-service data pipeline that can support plug-in data ingestion modules that improved our LLM model’s calibration timeline and our science team’s productivity by 300%.• Integrated 5+ client services and provided programming support for the back-end service to enhance the customer experience of our product which was accessed by over 30 million customers world-wide.• Mentored and solved complex technical issues that bubbled up when handling various tasks, resolved escalated issues from junior team members and all the while ensuring the code quality always met the highest standards.• Developed and delivered a cloud-based application that efficiently balanced job scheduling with allocated resources used by 5+ business teams, which ultimately reduced operational cost by 27% across the organization.

• Implemented the automated deployment process, thereby eliminating manual intervention and reduced overall release time for the newer versions by 40%.• Partnered with business engineers to develop an ETL tool that can handle multiple ETL workflows in sequence and feed the derivatives into their workflows, which improved processing time by 2x.• Documented all supported systems to account for all existing business procedures, and known bug fixes, helping on-calls and reducing the on-boarding time for new members.

• Built software application using Scala that seamlessly integrated with third-party brokerage systems to handle large scale streaming jobs and logging.• Created an interactive reporting dashboard which streamed live updates to help users manage their orders during operational hours, which surged user adoption (4x avg load).

• Developed scalable, low-latency responsive web models to perform real-time analytics on research data using JavaScript & jQuery.

• Developed scripts to parse excel spread sheets and crawl web sites to gather social data for sentiment analysis using Java.