About

Pratik Nandoskar is a highly skilled Software Engineer with over 5 years of experience in the industry. Currently, he works as a Software Engineer 2 at IQVIA, where he is responsible for developing Machine Learning algorithms to help Pharmaceutical companies detect Adverse Events. Pratik has an impressive track record in developing and designing Deep Learning models such as BERT and LSTM to classify Adverse events with an accuracy of 98.5%. He is proficient in data analysis of unstructured and text-based data and works with PHP, JavaScript, Python, MySQL, and NoSQL databases. Before joining IQVIA, Pratik was the Head of Product at Urbanholds, an upcoming ecommerce company providing urbanized products for home decor. During his tenure, he led the team and increased the company's revenue by 700% through efficient solutions derived from Social Media Advertisements. Pratik has previously worked as a Data Scientist at Kiswe Mobile, where he worked on Hangtime, a trivial quiz app, and developed Machine Learning models to identify bad actors in the chat room. He also worked on textual data generated by users in a chatroom and built a TF-IDF model to gain insights from the text. Pratik has experience in data visualization of textual data and worked as a Data Integration Specialist at Kuebix, where he developed REST and SOAP real-time APIs and ETL integration processes between technologies such as IBM Web Sphere and Salesforce. Pratik holds a Master's degree in Business Analytics and Information Technology from Rutgers Business School and a Bachelor's degree in Information Technology from the University of Mumbai. He has a diverse tech stack that includes ML, Python, JavaScript, PHP, NoSQL, SQL, Integration, Deep Learning, MySQL, Frontend, Backend, Data Scientist, Research Scientist, Salesforce, ETL, and Web. Pratik's expertise in software engineering and product management makes him an asset to any team. His ability to develop and maintain new APIs for integration and work with cross-functional teams on product development from planning to deployment and performance measurement is commendable.