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Driving future-forward innovation at the intersection of Workforce Tech and Preparation Tech - Crafting tools that empower the next billion to prepare, connect, and work
Builder at heart. Believer in hustle and systems that scale . Love building products with purpose - not just to solve problems, but to touch lives. On a mission to simplify how people get hired, get paid, and get growing. With over 10+ years of experience across I’ve led cross-functional teams to bring bold ideas to life - products that are intelligent, intuitive, and deeply human. From being a startup founder to leading enterprise-scale innovations, my journey has been driven by a single question: How can we make technology feel more like magic - seamless, meaningful, and trusted? I thrive where empathy meets innovation. Where product decisions are grounded in real user voices. Where data tells a story and design thinking breathes life into raw ideas. But more than tech, I care about people - their needs, frustrations, and aspirations. I believe in products that don’t just function, but resonate. Off the screen, I’m a travel lover, data geek, cricket fan, Tea lover and philosopher at heart. Always learning, always iterating. Let’s connect if you’re building something bold - or just want to talk about the future of AI and product innovation.
International School of Engineering (INSOFE)
Post Graduate Programme, Artificial Intelligence
January 1, 2017 – January 1, 2017
Amity University
Bachelor's degree, Mechanical & Automation Engineering
January 1, 2011 – January 1, 2015
Narayana juniour college
XII th, PCM
January 1, 2009 – January 1, 2011
City Central School
SSC, X th
January 1, 2008 – January 1, 2009
Freela
Building Freela
July 1, 2024 – Present
3AI Holding
Gen AI Product Manager
May 1, 2024 – June 1, 2024
Remote
ONPASSIVE
Product Manager
June 1, 2021 – April 1, 2024
Hyderabad, Telangana, India · On-site
Nimmetry Inc
Technical Product Manager - AI & ML
November 1, 2020 – May 1, 2021
Hyderabad, Telangana, India · On-site
RightData
Technical Product Manager
June 1, 2020 – August 1, 2020
Hyderabad, Telangana, India
InnovateMR
Data Consultant
February 1, 2020 – May 1, 2020
Ahmedabad, Gujarat, India
ProDevBase Technologies
Data Scientist
February 1, 2019 – January 1, 2020
Hyderabad, Telangana, India
UPPSTEAM (SteamRoller Technologies Pvt. Ltd.)
Data Scientist
February 1, 2018 – November 1, 2018
Greater Hyderabad Area
AgricxLab
Computer Vision
September 1, 2017 – November 1, 2017
Mumbai Metropolitan Region · Remote
GreyOrange
Consultant (Operations)
May 1, 2016 – April 1, 2017
Gurugram, Haryana, India
SYNERGIES CASTINGS LIMITED
Project Engineer Research & Development , Analytics
September 1, 2015 – April 1, 2017
Vishakhapatnam Area, India
Automalleable
Industrial visit
December 1, 2014 – December 1, 2014
Jaipur, Rajasthan, India
Amity Education Group
Student Placement Co-ordinator(CRC)
July 1, 2014 – May 1, 2015
Amity University
BHEL
Intern
June 1, 2014 – July 1, 2014
Visakhapatnam, Andhra Pradesh, India
Envivora
Founder
February 1, 2014 – June 1, 2015
Remote
Bosch
Industrial visit
November 1, 2013 – November 1, 2013
Jaipur Area, India
Ashok Leyland
Internship
June 1, 2013 – July 1, 2013
Chennai Area, India
Autodesk
Autocad Designer , Solidworks , Ansys
June 1, 2013 – July 1, 2013
Chennai Area, India
Automatic Defect Recognition in X-ray Testing using Computer Vision
January 1, 2018 – Present
To ensure safety in the construction of important metallic components for road worthiness, it is necessary to check every component thoroughly using non-destructive testing.In last decades, X-ray testing has been adopted as the principal non-destructive testing method to identify defects within a component which are undetectable to the naked eye. Nowadays, modern computer vision techniques, such as deep learning and sparse representations, are opening new avenues in automatic object recognition in optical images. These techniques have been broadly used in object and texture recognition by the computer vision community with promising results in optical images. However, a comprehensive evaluation in X-ray testing is required. In this paper, we release a new data set containing around 47.500 cropped X-ray images of 32 × 32 pixels with defects and no-defects in automotive components. Using this data set, we evaluate and compare 24 computer vision techniques including deep learning, sparse representations, local descriptors and texture features, among others.
Factory and demand side analytics
August 1, 2017 – September 1, 2017
Manufacturing data analytics can significantly benefit from the use of modeling and simulation. Simulation models of manufacturing systems can be used to support data analytics in multiple ways. They can be used to support diagnostic analytics through the use of sensitivity analysis of factors influencing the performance, predictive analytics by estimating future performance based on planned inputs, and prescriptive analytics when used in combined simulation optimization schemes to identify the input settings that lead to the goal performance
Industrial Analytics Of Things In Manufacturing
April 1, 2017 – Present
Technology of Smart Sensors, Robotics & Automation, Augmented/Virtual reality, Big Data Analytics, Cloud Integration, Software applications, Mobile, Low power Hardware devices and Scalability of IPv6-3.4X 10^38 IP address, etc.is a major driver for the Industrial Internet.It also has the potential to drive productivity and reduce operating costs across multiple industries, including manufacturing, health care, and mining.
Low Cost Automation
September 1, 2015 – April 1, 2017
Low Cost Automation is a technology that creates some degree of automation around the existing equipment, tools, methods and people, using mostly standard components available in the market.
Aerodynamic Simulation Of Bullet
October 1, 2014 – May 1, 2015
Hallo, I'm currently investigating in the Aerodynamics of a flying bullet. I'm quite comfortable with the set-up I use. The bullet analysis is for speeds up to 3 Mach, attack angles up to 6 degrees, and a rotational bullet (wall) of up to 22 000 rad/s. The results I get is almost acceptable, except the force in z direction and moment around y-axis on the centre point of bullet (Magnus force and Magnus moment). These values jump around a lot and never converged to the same value even if the same conditions is run again. I have a feeling this is about the mesh, I'm currently just using the meshing system inside ANSYS with just the default inflation from the body towards a greater outfield. I tried to refine the mesh around the bullet and inflate more and more gradually with extensive bodies but with no luck. when I ran the simulation in Fluent I get an "Floating point f" error. I really tried a lot of different meshing techniques with no luck I also know the "floating point f" error can be because of lost units...
Certified Expert In SaaS Analytics
Chargebee
June 25, 2026 – Present
IBM Blockchain Essentials
IBM
June 25, 2026 – Present
Deep Learning with TensorFlow
cognitiveclass.ai
June 25, 2026 – Present
Computer Vision With OpenCV Library Using Python
Udemy
June 25, 2026 – Present
Hands On Tableau For Data Science
Udemy
June 25, 2026 – Present
Product Manager Skills
Udemy
June 25, 2026 – Present
Google Analytics for Beginners
Google Digital Academy (Skillshop)
June 25, 2026 – Present
Advanced Google Analytics
Google Digital Academy (Skillshop)
June 25, 2026 – Present
Introduction to Data Studio
Google Digital Academy (Skillshop)
June 25, 2026 – Present
Startup
Startup School Online
June 25, 2026 – Present
AI Marketing Professional
Contlo
June 25, 2026 – Present
Katalyst 2.0
Keka HR
June 25, 2026 – Present
HubSpot Email Marketing
HubSpot Academy
June 25, 2026 – Present
AI For Product Management
Pendo.io
June 25, 2026 – Present
Product Analytics Micro-Certification
Mixpanel
June 25, 2026 – Present
SaaS Master Class : Sales , Marketing & Growth Metrics
Udemy
June 25, 2026 – Present
Product Strategy
Product School
June 25, 2026 – Present
MBA By Horoun
Udemy
June 25, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from computer vision in manufacturing to sports analytics and waste management, indicates a broad interest and adaptability. Their experience in various company sizes (startups to larger organizations) and roles (Data Scientist, Product Manager, Consultant) suggests a willingness to engage with different challenges and environments. The focus on AI/ML and data-driven solutions aligns with a forward-thinking, innovation-oriented culture. However, the target role of 'Data Analyst' is a significant shift from their recent senior Product Manager roles, which might indicate a mismatch in career trajectory or a desire to return to a more hands-on technical role. The lack of specific technologies listed for many projects makes it hard to fully assess the depth of technical cultural fit.
Soft Skills & Operational Fit
The candidate's experience in product management roles, particularly in agile environments, suggests strong organizational, leadership, and cross-functional collaboration skills. Their entrepreneurial background (Envivora, Freela) indicates initiative and problem-solving abilities. The descriptions of implementing work tracking tools and managing product roadmaps point to an operational mindset focused on efficiency and strategic planning.