About Susmitha Yanamadala
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Viewed 447
About me
Experienced Data Scientist with 4 years of industry expertise, adept in implementing advanced machine learning and deep learning solutions, including recommendation systems, natural language processing, and computer vision. Demonstrated leadership in executing Azure Data Platform projects, excelling in client collaboration and agile project management.
Education
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- 2023
University At Buffalo, The State University of New York
MS in Data Science
GPA: 3.83/4 • Relevant Course Work: Statistical Data Mining, Probability, Machine Learning, Reinforcement Learning, Computer Vision
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- 2018
VIT University
B.TECH in Electronics & Communication Engineering
GPA: 3.55/4 • Relevant Course Work: C Programming, Data Structures, Digital Signal processing, Digital Image Processing
Experience
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2020 - 2022
Sonata Software Limited
Lead Digital Engineer
• Led a team in the development of Azure-based platforms, enhancing ERP data export and usability through Azure integration.
• Automated pipelines in ADF and Synapse, accomplishing an 80% reduction in data processing time via parallel operations.
• Oversaw sprint task distribution, JIRA board management, and collaborated with cross-functional teams for efficient project flow.
• Saved $60,000 project-wide and cut $5,000 in monthly operational costs by managing budgets and utilizing Azure cost predictions.
• Pioneered PowerBI and Customer Insights sessions, advancing team and client data analytics skills. -
2018 - 2020
Sonata Software Limited
Data Scientist
• Achieved 94% accuracy in email classification using TFIDF with random forest and 85% in car damage detection with CNN.
• Developed demand forecasting model utilizing sales data, leading to a 10% decrease in stockouts and improving inventory planning.
• Implemented a soft ensemble classifier using decision tree and random forest, obtaining 96% accuracy for flight measure prediction.
• Initiated the creation of FERRETML, an automated machine learning tool that spans from data preprocessing to model deployment.
• Integrated Google speech recognition in QSR Voicebot, elevating order accuracy and personalized food recommendations.
• Leveraged Azure Databricks for Market Basket Analysis in retail, integrating data for insightful customer and product clustering.
• Designed REZOPIA, a travel recommendation system, employing historical data to refine destination suggestions for customers.
• Deployed REST APIs for application integration, and conducted A/B testing for performance optimization.