Building a SaaS product for cargo flows (ETA prediction) and Demand Forecasting (Air and Sea).
Hands-on (python): interpretable machine learning, time series forecasting at scale, unsupervised learning
Team management: have been leading data science team at the company. Managing the team of 4, have mentored several interns over time.
Project management: Executed projects, trials, and POCs with some of the leading freight forwarders, manufacturers, cargo carriers, and shipping companies that have contributed towards overall ARR.
Checkout:
1. Container Visibility
2. Demand Forecasting
3. Tech Blog
Have been part of an early-stage team that delivered for the first client of noodle.ai. The team dealt with social network big data (in range of TBs). Built, evaluated, and shipped recommendation system.
Developed a composite index and a risk engine as hedging tools to address the problem of raw material price volatility. link
Developed a demand prediction engine for a Private Jet airline. link
- Helped the pre-sales team to pitch ideas, in preparing demos
- Prepared training materials
- Product development
- Mentored interns, new hires
Wrote code for various modules of Next Generation FireWall including NAT, DHCP, Syslog
Design, Sustenance, Unit and Integration testing
Addressed high severity customer queries and issues
Collaborated with network security research teams to identify, implement data science use-cases (Malware classification, integrating machine learning based IPS etc. - github)
Prepared Internal surveys that help executives make decisions
Part of ThingQbator (IoT makerspace)
Finished products are for decadent minds.
His was an evolving mechanism and second foundation was an instrument for that evolution
- Foundation
