A passionate
Data Analyst with 3+ years of experience designing dashboarding (Power BI, Tableau) solutions and writing optimized SQL queries. I specialize in analystics to drive business objectives, with a proven track record of taking full ownership of BI projects from requirements gathering to deployment while ensuring data accuracy.
With an MSc in Business Analytics (Machine Learning) from UMass Lowell (4.0 GPA), I've applied my analytical toolkit—Python, R, SQL, Tableau, and Power BI—across finance, supply chain, healthcare, and data engineering projects. My experience spans building scalable data pipelines with PySpark, creating ML infrastructure on AWS, and developing automated dashboards that accelerate decision-making by up to 40%.
What sets me apart is my ability to translate complex data into actionable insights for both technical and executive stakeholders. Whether it's improving data accuracy to 98%, reducing reporting time by 35%, or building AI chatbots with NLP, I thrive on transforming raw data into business impact.
Aug 2023 - May 2025
Awards: GPA of 4.00, Beta Gamma Sigma
Coursework: Decision Analytics, Advanced Data Mining, Advanced Machine Learning, Database Management, Statistics for Predictive Modeling, Optimization, Storytelling with Data
Data professional with 3+ years specializing in BI solutions, dash boarding, data engineering, and analytics. Proven track record of building scalable data pipelines, improving data accuracy to 98%, and accelerating decision-making through automated dashboards and predictive analytics.
Here are some of my key projects showcasing my expertise in data analysis, machine learning, business intelligence, and visualization.
This project focuses on using SQL for pricing optimization and linear regression to help businesses determine the optimal price point for maximizing revenue.
Developed a framework to quantify operational volatility in 2.4M+ deal records, enabling predictive analytics for high-risk scenarios.
Built a custom RAG-based AI chatbot to answer queries from UMass Lowell's MSBA program pages using sentence-transformers and feedback loops & is designed for accurate context retrieval, dynamic response generation, and scalable deployment.
Built a cancer document classifier using classical ML, ensemble models, and CNN. Achieved 97% accuracy on biomedical abstracts for Lung, Colon, and Thyroid cancers.
Analyzed user behavior from real e-commerce data using A/B testing, segmentation, and retention modeling & uncovered insights on user value and lifecycle trends through cohort and revenue analysis.
Pioneered novel market prediction research combining sentiment analysis with Double Machine Learning to uncover hidden patterns in S&P 500 and Russell 3000 indices.
Engineered a risk-optimized investment strategy achieving 91.8% better returns than S&P 500, leveraging CAPM and advanced portfolio analytics.
Demonstrates how predictive analytics and supply chain simulations can optimize inventory management and improve forecasting accuracy.
Utilized CTEs, temp tables, and views to perform in-depth analysis of COVID-19 data.
Collection of interactive dashboards covering various business intelligence and analytics topics.
Performed EDA on world population data, leveraging Seaborn for visualizations and outlier detection.
Utilized Matplotlib to visualize Ice Cream Ratings data with heatmaps and bar plots.
Used BeautifulSoup to scrape Wikipedia data, clean it, and save it as a structured CSV file.
Here's an overview of my technical proficiencies and professional certifications.
I love learning new technologies! For more details, check out:
Feel free to reach out to me for collaborations, job opportunities, or any inquiries!
+1-978-375-****