Mayank Jha
Chief Executive Officer at GNC India
Mumbai, Maharashtra, India
Summary
🤩
Rockstar🎓
Top SchoolMayank Jha is a seasoned executive and entrepreneur with 13 years of experience building consumer-facing digital businesses and health & wellness infrastructure in India, currently leading GNC India as CEO. He combines a strong analytical background from IIT Delhi and ESCP with hands-on product, growth and e-commerce leadership—scaling marketplaces, performance marketing, CRM and P&L responsibilities. Earlier roles include founding tech-driven startups, driving community growth at Roposo to 2M+ monthly active users, and leading digital transformation at consumer brands. Mayank also has technical contributions as a back-end/DevOps contributor to high-profile open-source infrastructure like NVIDIA’s AIStore, improving backend features and release workflows. He is driven by a clear mission to help Indians attain peak performance through better nutrition, and applies continuous experimentation and operational rigor to turn that vision into measurable consumer outcomes. His uncommon blend of finance, startup-building and engineering experience lets him bridge strategy, product and execution effectively.
13 years of coding experience
7 years of employment as a software developer
Indian Institute of Technology Delhi (IIT Delhi)Masters in Management, Finance, Masters in Management, Finance at ESCP Business School
English, French, Hindi, Maithili
Github Skills (12)
go10
api-design9
restful-api9
devops9
kubernetes-pods9
rest-api9
automations9
automation9
api-rest9
object-storage9
kubernetes9
regular-expression8
Programming languages (11)
Github contributions (5)
NVIDIA/aistore
May 2020 - Sep 2020
AIStore: scalable storage for AI applications
Role in this project:
Back-end Developer & DevOps Engineer
Back-end Developer & DevOps EngineerContributions:92 commits, 18 pushes, 1 branch in 3 months
Contributions summary:Mayank's contributions primarily focused on enhancing the AIStore backend by introducing new functionalities and improving existing components. This includes adding bucket name filtering using regular expressions and improving tabular views. The user also worked on features like creating and removing buckets with an "ignore error" option. Furthermore, the user has integrated with the DevOps area by introducing the progress bar for chunked object put operations, enhancing the user experience, and adding code for the automated github release workflow.
scalabledeep-learningdistributed-shufflemachine-learninghyper-converged
mjnovice/mjlang
Dec 2014 - Nov 2018
Contributions:6 commits, 3 pushes in 3 years 11 months
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