Ravi Prakash Singh
About Ravi Prakash Singh
Ravi Prakash Singh is the Director of Data Science, Generative AI at Asurion, specializing in leveraging AI to enhance customer experiences. He has extensive experience in data science, having worked in various roles across multiple industries.
Company
Ravi Prakash Singh is currently working at Asurion, a global tech care company, as the Director of Data Science focusing on Generative AI. He is based in Nashville, Tennessee, United States. Prior to his current role, he was employed at Asurion in various capacities, including Senior Manager, Data Science, and Data Scientist.
Title
Ravi Prakash Singh holds the title of Director, Data Science, Generative AI at Asurion. He has been serving in this role since 2023. His work revolves around leveraging Generative AI to enhance customer experiences in messaging and voice/IVR channels.
Education and Expertise
Ravi Prakash Singh completed his Master's degree in Analytics - Data Science from Georgia Institute of Technology in 2019. He holds a Bachelor's degree in Chemical Science & Technology from the Indian Institute of Technology, Guwahati, achieved in 2014. His technical prowess includes proficiency in libraries such as Scikit-learn, PyTorch, TensorFlow, OpenCV, and spaCy. He also utilizes Python, R, SAS, and SQL Server Business Intelligence Development tools for data science and analytics tasks.
Professional Background
Ravi Prakash Singh's professional journey includes various significant roles. He worked at The Home Depot as a Data Science Intern in 2019, and at Georgia Institute of Technology as a Graduate Teaching Assistant. He also served as an Associate Manager in Modelling & Analytics at Standard Chartered Bank, and as a Senior Data Analyst and Data Analyst at Kabbage, Inc. His career started as a Trainee Decision Scientist at Mu Sigma Inc. He has also held intern positions at Université de Montréal and Reliance.
Skills and Specializations
Ravi Prakash Singh specializes in leveraging Generative AI to enhance customer experiences. He has expertise in optimization, simulation, and statistical modeling, which he has applied in various industries such as insurance, credit and risk, and retail. His data science projects employ tools and languages including Python, R, SAS, and SQL Server Business Intelligence Development tools, and he has experience leading teams as well as working as an individual contributor.