Hi, I'm Hrishikesh Pawar
I'm an aspiring data professional pursuing a Master's in Data Analytics and Management. Skilled in Python, AWS, and Azure cloud technologies, I aim to contribute to innovative, data-driven solutions in cloud and data environments.
About Web-Experience - Currently, I have been enrolled in ITMD 541 to strengthen my knowledge in web applications.
Skills
- Python
- SQL, Linux, pySpark
- AWS, Azure Cloud
- Microsoft PowerBI, MS Excel
Education
Illinois Institute of Technology, Chicago, IL (Expected Graduation May 2025) - Master’s in Information Technology and Management, Specialization in Data Analytics and Management.
University of Mumbai, India - Bachelor of Engineering (Mechanical Engineering)
Projects
Spotify API Data Pipeline: Developed a scalable pipeline using Apache-Airflow on AWS services.
Application Load Balancer Logs Data Analysis: Analyzed AWS ALB logs, handling 3000+ server requests.
AWS-services-Implementations: Contains AWS LABS
KPI-analysis-of-an-E-commerce-store : Data analysis and visualization on a dataset of e-commerce orders from November 2022 to February 2023.
Experience
Student Researcher: AI Development | Illinois Institute of Technology, Chicago, IL (August 2023 – September 2023)
- Developed and fine-tuned an AI-driven Intrusion Detection System (IDS) using SecBERT and Isolation Forest models, achieving 79% accuracy in detecting sophisticated cyber threats.
- Collaborated to design and implement a SecBERT-based one-class classification model, reducing detection loss by 15% with dropout and weight decay techniques.
- Engineered Python scripts to process 124 million+ rows of data, reducing latency by 25% and boosting anomaly detection accuracy by 20%.
Data Analyst Intern | VEmpower Global Strategy Services LLC (Remote, July 2023 – August 2023)
- Served as a Project Scribe in an Agile 9-member team, analyzing Facebook's SuperHeroU campaign data using Power BI.
- Analyzed KPIs for 11 campaigns, resulting in a 14.5% increase in income and improving performance among the 18-24 demographic.
- Optimized audience segmentation by excluding ineffective campaigns, significantly boosting overall campaign performance.
Cloud Data Engineer Trainee | StormSofts Technology Software Development Company (Hybrid, June 2022 – June 2023)
- Managed 5+ AWS resources, achieving 99.9% uptime, reducing costs by 15%, and improving application load time by 20%.
- Designed scalable data pipelines for Alphabet News, enhancing data integration by 25% and reducing deployment time by 40%.
- Enhanced user experience by optimizing the Alphabet News app, leading to faster load times and higher user satisfaction.
Project Intern | Validus Analytics LLP, Pune, Maharashtra (June 2021 – February 2022)
- Applied TinyML technology to automate processes, achieving 87% accuracy on a deep learning CNN model.
- Developed a solar panel image classification model with 98% accuracy on training and validation datasets.
- Optimized model size by 65% using TFlite, enabling deployment on BLE 33 Sense devices with real-time classification via Gradio GUI.
