Rani Mathialagan

Experience

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  MResult

  Jun 2005 - now

  PharmScience – Bio Therapeutics: MAUDE - NLP based Machine Learning ClassifierMAUDE – Manufacturer and User facility Device Experience – Data collection represents reports of Adverse Events involving Medical Devices. Each year the FDA receives several hundred thousands Medical Device Reports (MDR) of suspected device associated deaths, serious injuries and malfunctions. Our solution includes NLP based Machine Learning algorithm to label & categorize the adverse events. Our analysis and outcome includes frequent occurring problems associated with the device, critical problems that could have led to patients death, what are the new problems that are reported in the recent past ?, and any opportunity that exists for the improvement of the device.The classification and labelling was performed using key words obtained from the “Event Description” text data from MAUDE database.Applied: ML Classification Algorithm, Python, AWS Sagemaker Show less - Performing EDA , building LSTM models and forecasting Price for Government Market commodity data. - Statistical test and Analysis of “Road Accident Report for multiple years”- Identify the important features of a cell phone to decide the price range using various ML Classification - Created a storyboard, computed table calculations and dashboards using Infectious-disease dataset- Analyze and Visualize Big Mart ecommerce data - Developing Conversational AI Chatbot for Government portal with farmers FAQs in RASA(ongoing)Participated in Hackathons : - NLP (Conversation Generating Model with Similarity Score) - Deep Learning (Fake vs Real Image Detection Challenge ) - Machine Learning ( Identify similar patients with Silhouette score) Show less

  • Manager - Data Scientist

    Nov 2022 - now

  • Senior Data Analyst / Data Scientist

    Jun 2005 - Apr 2023