About

Sharmila Vadlapudi is a highly skilled Senior Associate at Cognizant with over 10 years of relevant experience in the field of data science and software engineering. She is currently working on a sales opportunity age prediction model for Microsoft, where she has developed decision tree and random forest models. Additionally, Sharmila is also working on text mining techniques such as topic modelling, web n-grams, POS-tagging, and text summarization to derive insights from seller-filled surveys. In her previous role as a Software Developer at Kaptron, Sharmila developed a modified K means algorithm for clustering warships based on direction and speed. She used the elbow method to identify the optimal number of clusters to be created and optimized the algorithm for delivering real-time performance. Sharmila's educational background includes an M.Sc Integrated Maths & Scientific Computing from IIT, where she focused on Maths & Scientific Computing. She has also gained expertise in various tech stacks such as Random Forest, Parts-of-speech, Web, and Software Engineering. At Cognizant, Sharmila has also worked on a Healthcare POC project, where she formulated use cases from medical and pharmacy claims data. She developed models for predicting high-cost patients using medical claims data for two diagnoses and used logistic regression and decision tree for classification. Additionally, she also developed models for predicting drug adherence of a patient from pharmacy and medical claims using GBMs. She trained GBM at slow, medium, and high rates and used the ensemble of these models. Overall, Sharmila is a dedicated and highly skilled professional who has excelled in her field of work. Her expertise in data science and software engineering makes her a valuable asset to any organization.