Head of data science at Portcast.io
previously: @NoodleAi, @Cisco, mentor @Springboard
8 years of hands-on and 4 years of leadership experience
Launched products, deployed machine learning, have led, grew teams at startups
Machine Learning, MLOps, product development, management, cross-functional collaboration
Building a SaaS product for cargo flows (ETA prediction) and DemandForecasting (Air and Sea).
Started working with founders from early stage of the company (seed round-team of 4 full time including founders), helped company in achieving product market fit, shaping-scaling product and growing data science/tech team.
Hands-on: interpretable machine learning, time series forecasting at scale, supervised and unsupervised learning, cloud services (aws, google cloud),data pipelines. Proficient with Python, SQL
Project/Product 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.
- Conducted, assisted in feasibility studies and experiments to translate ever growing Portcast data in new product features.
Team Lead/ Manager: have been leading the remote data science team at the company. working, growing and learning with the team of 9 (4 different nationalities) including data analysts, data engineers, data scientists and interns.
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