Roy Chowdhury
Founder & CTO at Investify Limited
Auckland, Auckland, New Zealand
Summary
👤
Senior🎓
Top SchoolRoy Chowdhury is a founder and CTO with 8+ years of leadership experience building data-driven products and platforms at the intersection of Data, AI, and Fintech from Auckland, New Zealand. He leads Homely, a digital mortgage assistant using AI and open finance to simplify home loans, while running Datapoints across ANZ to deliver managed data engineering, governance, and MLOps for trusted, explainable AI. His background spans banking and consulting roles where he built enterprise BI and analytics organizations, led multi-country finance data platforms, and scaled teams of 60+ data professionals. Roy combines strategic vision with hands-on delivery—specializing in generative AI, computer vision, IoT analytics, and the integration of people, process, and platforms. He’s entrepreneurial and pragmatic, having spun multiple ventures and partnerships to bring advanced analytics into production-grade solutions. Despite a primarily commercial focus, he remains a problem-seeker at heart, actively looking for thorny technical challenges to solve.
8 years of coding experience
5 years of employment as a software developer
B.Com Accounting, B.Com Accounting at St. Xavier's CollegeMasters of Management Finance, Masters of Management Finance at The University of Waikato
English, Bengali, mandarin (basic)
Github Skills (39)
polygons10
bounding10
classify10
points10
sketch10
annotations9
bounding-box9
drawing9
diagram9
sdk9
react8
collaboration8
health8
blockstack8
image-annotation8
Programming languages (6)
Github contributions (5)
Xkey-AiEstimation/react-image-annotate-1
Aug 2023 - Mar 2025
Create image annotations. Classify, tag images with polygons, bounding boxes or points.
Contributions:1 review, 177 PRs, 206 pushes in 1 year 8 months
polygonsannotationsimage-annotationsboundingboxes
CMPUT301F18T25/HealthX
Oct 2018 - Dec 2018
Cmput301 Class Project
Contributions:103 commits, 34 PRs, 68 pushes in 1 month
javascriptclass-project
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