Internship Summary - CBRE
Welcome to my Data Science Project Portfolio!
As a data enthusiast with a background in biotechnology and a Master's in Data Science, my journey in the data field has been nothing short of exhilarating. I've had the privilege of applying data-driven methodologies to a myriad of contexts, spanning biotechnology, supply chain optimization, spend analytics, construction management, and investment strategies.
My diverse experiences have not only broadened my horizons but also honed my skills in extracting actionable insights from data. Join me on this expedition through a spectrum of data-driven projects, where we explore the dynamic interplay of data and its profound impact on diverse industries.
Together, we'll delve into the art of turning complex data into valuable knowledge, just as I've done in my journey. Let's embark on this data-driven adventure and discover the limitless possibilities that data science has to offer!
Master of Science, Business Analytics, Data Science Cohort
Deans Excellence New Student Cohort Scholarship, Microsoft Student Ambassador
GPA 3.8/4
Bachelor of Technology, Biotechnology
Relevant Courses: Problem Solving and Computer Programming, Biocomputing, Bioinformatics
GPA 8.2/10
• Developed a budget prediction model using XGBoost regressor, Random Forest regressor, and Neural networks for Asset data, achieving a commendable 89% R-square value.
• Designed and implemented a user-friendly dashboard and UI to enhance data visualization.
• Utilized Regrid and Local Logic database APIs to efficiently retrieve and analyze site data and demographic information, supporting data-driven decision-making.
• Conducted extensive market research on Spend Analytics and Accounts Payables solutions.
• Extracted data from Snowflake schema and presented the analysis on an extensive PowerBI dashboard.
• Generated insights on tail and maverick spending that can cut annual expenditures by 5-10% on average.
Facilitating a mentorship program involving 1000+ students and other events to help students on campus.
• Individual bronze medalist and 4th place in the InterNIT Team Championship.
• Successfully managed tournament sponsorships and coordinated logistical operations for events.
• Developed a credit card strategy by comparing XGBoost and Neural Network models on historical data.
• Chose XGBoost as the final model due to superior performance with AUC of 0.93.
• Determined conservative and aggressive strategies based on model output to achieve desired default rate and revenue balance.
•Proficiently conducted web scraping from Zillow and Trustpilot to obtain real-world data.
•Expertly preprocessed data to eliminate biases and duplicates.
•Conducted Sentiment Analysis and presented consumer sentiment insights through a dashboard with tailored KPIs and metrics.
• Analyzed Conagra's table spreads sales data, comparing loyalty and performance against competitors.
• Identified the largest buyer group as middle-class, retired, and married females and recommended tailored marketing strategies. Recommended promoting 16-ounce Stick-form products to improve sales.
• Performed time-series analysis on sales data to predict sales for 2024 and 2025