Empowering change by unveiling data’s potential to inform, inspire, and make an impact – this is where I thrive.
Currently in Boston, MA
My digital DNA includes
Python
Life Lately
Masters at Northeastern University
The Inside Scoop
Currently developing a Digital Twin for predictive healthcare monitoring
Do you want to start a project together?
A showcase of recent works
Hungry Foods
A food delivery or recipe app, that allows users to browse, discover, and order food or view recipes, enhancing their food exploration experience
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Electric vehicle Data Insights
Electric vehicle data analysis using statistical tests and algorithms, achieving 97% accuracy in trend prediction for strategic insights
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HR Analytics Strategy
Analyses of HR Data to develop strategies that enhance workforce efficiency, retention, and overall employee satisfaction
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Store Analysis
Store Data Analysis to identify trends, optimize inventory, and improve sales strategies, supporting better decision-making for retail performance.
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How I tech traversed my way here
Master of Science in Data Analytics
Northeastern University
- GPA: 3.83
- Discover opportunities to improve systems, processes, and enterprises through Data Analytics
- Relevant Coursework:Computation and Visualization for Analytics, Data Mining in Engineering,Foundations for Data Analytics Engineering, Data Management for Analytics
Data Support Engineer
HP Inc.
- Collaborated with cross-functional teams and data scientists to develop a recommendation system that improved the accuracy of resolutions by 96%
- Resolved majority of the issues on the first contact using ML algorithms to predict and identify recurring issues, leading to a 90% reduction in ticket resolution time
- Implemented remote diagnostics tools to detect and troubleshoot hardware/software issues, minimizing the need for on-site support up to 90% of the times
Data Science Intern - Machine Learning, OpenCV based
Basal Analytics
- Collected and pre-processed vaccination data from multiple sources, applying statistical techniques to analyze vaccination rates, demographic coverage, and vaccine efficacy across various health centers, resulting in a 90% improvement in data accuracy
- Collected a dataset of chest X-rays and trained a ResNet-50 model to classify lung diseases, achieving 97% accuracy and an AUC of 0.89 in disease identification
B.Tech in Electronics and communication
Acharya Institute of Technology
- Apply discrete and continuous probability distributions to demonstrate the validity of testing the hypothesis
- Analyzed and modeled the Random events in typical communication events to extract quantitative statistical parameters
- Associated with Non-Profit organizatios(AICTE) to help students who lacked educational support