Welcome to my GitHub profile! I’m a passionate Data Scientist and Machine Learning Innovator with a strong foundation in Data Science, complemented by a love for finance & healthcare research. Here, you’ll find my work at the intersection of AI, machine learning, and analytics.

• Johns Hopkins University
  Master of Science in Data Science (Expected: 2026)
  Relevant Courses: Advanced Data Science, Machine Translation, ML for Healthcare

• LM Thapar School of Management
  MBA in Finance (2024)
  Relevant Courses: Financial Derivatives, Options Pricing, Portfolio Management

• Thapar University
  Bachelor’s in Computer Science (2023)
  Relevant Courses: Deep Learning, Probability and Statistics, Algorithm Design

November 2024 – Present | Baltimore, USA
Developed robust algorithms for parsing and analyzing SEC filing data, utilizing Python and Stata to transform complex financial information and apply predictive modeling for enhanced analytical accuracy.

• Optimized Financial Data Extraction Developed financial data parsing algorithms using regex and data cleaning techniques to process unstructured data from SEC filings of BDCs
• Built pipeline for predictive modelling Applied Python and Stata to create a robust pipeline for validating and transforming complex financial datasets. Leveraged predictive modeling to forecast trends and generate actionable insights, boosting data accuracy for thorough downstream analysis

February 2024 – July 2024 | Noida, India
Pioneered customer insight-driven data pipelines and enhanced product strategies for one of the world’s leading electronics giants.

• Voice of Customer Analysis: Built dynamic web scraping solutions using Selenium and Beautiful Soup to extract customer feedback from major platforms.
• NLP Mastery in Action: Applied BERT fine-tuning for sentiment analysis and LDA for topic modeling, transforming unstructured data into actionable insights that elevated customer satisfaction.

August 2023 – September 2023 | Remote
Elevated intrusion detection accuracy with a cutting-edge video analytics system, driving enhanced security protocols.

• YOLO & Optical Flow in Sync: Implemented a hybrid approach using YOLO for object detection and Optical Flow for motion tracking, achieving a 30% improvement in detection precision for real-time systems.

June 2023 – July 2023 | Mumbai, India
Harnessed the power of big data to uncover engagement patterns and deliver data-driven marketing strategies for India’s top telecom provider.

• Scalable Data Processing: Created a Spark-based ETL pipeline that processed over a million tweets and integrated MongoDB for fast, efficient storage.
• Visual Storytelling with Tableau: Developed compelling visualizations that informed marketing strategies, boosting campaign effectiveness by 15%.

An innovative AI-powered solution for environmental management, featuring a patented system for waste classification.

• Smart Waste Management: Leveraged TensorFlow and ResNet on Raspberry Pi to accurately distinguish between biodegradable and non-biodegradable waste, achieving 93.07% classification accuracy.
• Impact in Action: This prototype advances environmental sustainability by improving waste segregation processes in water bodies.

• Programming Languages: Python, MySQL, R, C++, Java, JavaScript
• Technical Skills and Tools:
  • Data Filtration: NumPy, Pandas, OS, Scikit-Learn, SciPy, Datasets, LIWC, NLTK
  • Web Scraping: Selenium, BeautifulSoup
  • Model Building and Training: PyTorch, Transformer, WandB, SageMaker, SpaCy, Flair, TensorFlow, OpenCV, Amazon Lex, XGBoost
  • Data Visualization: Matplotlib, Seaborn, Tableau
• Software & Frameworks: PowerBI, Spark, Hadoop, AWS, Azure, Apache Spark, Docker, Microsoft Excel, Figma
• Competencies: Machine Learning, Generative AI, Feature Engineering, Deep Learning, Data Analysis, Financial Derivatives

• Millennium Fellowship 2021 by United Nations Academic Impact
• Head of Administration for IAESTE, TIET, India Chapter
• Top 5 Finalist in Microsoft Learn Student Chapter Hackathon at Thapar University

Whether you're interested in discussing a project, exploring collaboration opportunities, or simply want to chat about data science, feel free to reach out on LinkedIn or GitHub.