Sasank Dhulipudi

Dynamic Data Scientist and Data Analyst with over 5 years of experience in delivering innovative, data-driven solutions that enhance performance and drive revenue growth. Proven track record in optimizing decision-making through advanced analytics and machine learning methodologies. Holds a Master’s in Data Science from Pace University, focusing on leveraging technical skills for impactful results. Committed to continuous professional development and contributing to high-performing teams.

Results-driven professional with expertise in Artificial Intelligence, Machine Learning, Cloud Computing, and Predictive Modeling. Proven track record of developing transformative solutions that enhance human-computer interaction and push industry boundaries. Aiming to leverage skills at leading organizations such as Google, Amazon, Microsoft, and OpenAI while aspiring to establish a technology-oriented company in the next decade.

• Microsoft Certified: Azure Data Fundamentals
• Google Data Analytics Specialization (Data Preparation and Visualization)
• Analyzing and Visualizing Data with Microsoft Excel
• Introduction to Data Analysis using Excel
• Analyzing and Visualizing Data with Microsoft Power BI

SIDE VIEW VEHICLE DETECTION METHOD — Research focused on innovative detection methodologies.

• Built a sophisticated platform using Python and Tableau to enhance data analysis for healthcare applications.
• Leveraged predictive modeling to detect health trends, increasing analysis efficiency by 40%.
• Designed real-time dashboards providing actionable insights for healthcare decision-makers.

• Developed a Cloud Data Warehouse (AWS, Tableau) to streamline sales analytics and inventory forecasting.
• Improved demand forecasting and reduced inventory shortages by 30%.
• Designed data visualization tools for enhanced reporting efficiency.

• Engineered a high-performance fraud detection system using Isolation Forest & XGBoost.
• Reduced fraudulent transactions by 35% with robust monitoring and alerting mechanisms.
• Enhanced data security through real-time anomaly detection.

• Built an NLP-powered platform using Python and Tableau for sentiment analysis of customer feedback.
• Improved customer satisfaction insights by 25% through predictive modeling and text analytics.
• Automated review categorization for better decision-making.