Surabhi Nivas

Analytical Data Analyst with a strong background in pharmaceutical sciences and patient safety, transitioning from academia and healthcare into the field of data science. Skilled in utilizing Python for quantitative analytics and data transformations, with a focus on scenario modeling and forecasting using large datasets. Excited to apply expertise in data science to revolutionize healthcare models and provide advanced analytics services.

• Collaborated with licensed pharmacists to process prescriptions and manage inventory in a GMP environment.
• Analyzed inventory trends to predict medication needs accurately
• Enhanced patient care by error-free processing of 100+ daily prescriptions.
• Maintained zero out-of-stock levels for all medications, both controlled and non-controlled.
• Streamlined prescription processing, ensuring error-free handling of 100+ daily.
• Develop and deliver undergraduate and post graduate courses.
• Implemented consistent evaluation methods, improving student feedback accuracy.
• Mentored students in research, boosting university service participation by 20%.
• Created standardized testing protocols, resulting in reliable and fair student assessments.
• Worked collaboratively with colleagues, students, and broader academic community to conduct academic conferences, workshops and seminars
• Publish research findings in reputable academic journals and present at conferences

Book Recommendation System: I as a Data Scientist at BookWise, an e-commerce book company, was provided with the task of building an AI-based nook recommendation system that utilizes customer data to provide personalized and relevant book suggestions. The primary goal of this system is to increase customer satisfaction and sales revenue by improving the shopping experience and helping customers discover new books they are likely to enjoy. I was successfully able to complete this project with proper recommendations. 

Food hub Order Analysis:The food aggregator company has stored the data of the different orders made by the registered customers in their online portal. They want to analyze the data to get a fair idea about the demand of different restaurants which will help them in enhancing their customer experience. I performed data analysis to formulate better strategic methods that will help the company to improve the business.