Passionate about Products, always curious, and enjoy connecting with people.
I started my career straight out of college as a Research Associate with a degree in Economics. After a year, I realized research wasn't the right fit for me, so I began exploring different fields and courses, from finance to marketing, trying to find my true passion. During this exploration, I discovered Product Management and immediately knew it was the direction I wanted to pursue.
I began in a UAT role to gain hands-on experience and understand how product teams operate. Within a year, I moved into an Associate Product Manager position and eventually took on the role of Product Manager, managing one team and later expanding to two teams, driving strategy, execution, and collaboration. Recognizing that the world of product and technology is constantly evolving, I enrolled in the MS-BAIM program at Purdue University to strengthen my technical skills and enhance my ability to build impactful, data-driven products.
My philosophy is simple: if something scares you, jump in. Growth happens when you face challenges head-on, learn along the way, and embrace uncertainty. I believe action and curiosity are the best teachers.
I try one new dish every week and keep iterating until I finally crack the code of a recipe that feels just right. Also, I love learning about how different yarns intertwine to form innovative textile products.
Technologies and competencies I work with
Pandas, NumPy for data manipulation and analysis
Database querying and data extraction
Tableau, Power BI, Excel for insights and reporting
Statistical analysis and insights generation
Experimentation and hypothesis validation
Predictive modeling and data science techniques
Azure DevOps, Productboard, Miro, Databases
Stakeholder management and communication
This project predicts company bankruptcy using financial and operational data. Applying data mining principles and ensemble ML techniques, it achieved a high AUC score in a Kaggle competition, securing 5th place among global participants.
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Analyzes startups to identify acquisition candidates using funding, revenue, growth, and valuation metrics. Includes EDA, visualizations, and ranking to provide actionable insights for venture capital investment decisions.
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Analyzes Twitter data to extract insights on user behavior, trending topics, and sentiment patterns. Using data cleaning, EDA, and visualizations to identify key trends, engagement metrics, and sentiment trends for social media strategy.
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Performs semantic analysis on wine reviews and descriptions, using MongoDB for data storage and NLP techniques like tokenization, word embeddings, and clustering to uncover patterns in flavor profiles and consumer perceptions.
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Performs a detailed analysis of Netflix's content data, exploring trends in movies and TV shows, release patterns, content types, genres, and regional distributions to uncover insights about Netflix's catalogue and viewing trends.
View on GitHubFeel free to reach out for collaborations or just a friendly hello! I'm currently looking for new opportunities to work on exciting projects. Whether you have a question or just want to say hi, I'll try my best to get back to you!