About Me
Hey there! I'm Pratham Patel, a Data Scientist with 2+ years of experience building production ML systems, NLP applications, and computer vision solutions. I'm skilled at translating business problems into deployed AI products that drive measurable efficiency gains for enterprise clients.
Beyond building systems, I'm passionate about growing people. I've led a cohort of 7 CS interns as their primary technical mentor — owning the onboarding curriculum, designing architecture training sessions on cloud-native AI platform design, and driving weekly progress reviews that accelerated intern ramp-up time by 50%. I set engineering standards and code review practices that were adopted across junior team members.
On the technical side, I've co-developed an enterprise no-code ML platform with a cross-functional team of 10–15 engineers, built AI-powered meeting assistants that save teams 3+ hours weekly, and deployed solutions across Fortune 500 organizations. I hold a B.Tech in Computer Engineering from Charotar University of Science and Technology (2020-2024).
Experience & Education
Data Scientist
Bacancy Technology
Ahmedabad, Gujarat
- Co-developed enterprise no-code ML platform with a cross-functional team of 10–15 engineers; owned the time series forecasting module — automated 7+ manual preprocessing steps including data shaping, feature engineering, and model selection, reducing baseline development time by 80%
- Architected and deployed AI meeting intelligence system using AssemblyAI for transcription and GPT-4 for summarization, action-item extraction, and decision logging — integrated with Google Calendar and Drive APIs to automate end-to-end documentation workflows, saving 3+ hours weekly
- Led a cohort of 7 CS interns as their primary technical mentor — owned the onboarding curriculum, designed and delivered architecture training sessions on cloud-native AI platform design, and drove weekly progress reviews that accelerated ramp-up time by 50%
Data Science Intern
Bacancy Technology
Ahmedabad, Gujarat
- Developed YOLOv8-based computer vision system for manufacturing defect detection, achieving 70% accuracy on metal surface anomalies — enabled automated quality control for production line inspection across varying lighting conditions and defect types
- Improved model robustness through systematic hyperparameter optimization using grid search and Bayesian tuning, increasing detection reliability across edge cases and reducing false positive rate
B.Tech in Computer Engineering
Charotar University of Science and Technology
Anand, Gujarat
Focused on computer science fundamentals, machine learning, and software development.
Skills & Technologies
Languages
Frameworks
Developer Tools
Libraries
Leadership & Mentoring
Want to know more?
Download my resume for a complete overview of my experience and skills.
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