Megha Sinha
About Megha Sinha
Megha Sinha is a Senior Data Scientist specializing in Natural Language Processing (NLP) at WhizAI, where she has worked since 2024. She has expertise in Named Entity Recognition, Sentiment Analysis, and machine learning models, and has previously held roles at Nokia and WhizAI as an NLP Engineer.
Work at WhizAI
Megha Sinha currently holds the position of Senior Data Scientist at WhizAI, where she has been employed since 2024. Prior to this role, she served as an NLP Engineer at the same company from 2021 to 2023. In her current role, she is involved in the cognitive intelligence team, focusing on the development and research of natural language processing (NLP) algorithms and data extraction techniques. Her work includes developing innovative solutions for business intelligence bots and resume recommender systems.
Education and Expertise
Megha Sinha completed her Master of Computer Applications (MCA) at the National Institute of Technology Jamshedpur from 2017 to 2020. She also holds a Bachelor of Computer Applications (BCA) from Magadh University, where she studied from 2013 to 2016. Additionally, she achieved an Intermediate in Science from Gaya College, Gaya, from 2011 to 2013. Her educational background provides a strong foundation for her expertise in natural language processing, particularly in tasks such as Named Entity Recognition, Sentiment Analysis, and Text Classification.
Professional Experience
Before joining WhizAI, Megha Sinha worked as a Graduate Engineer Trainee at Nokia for five months in 2020. She also completed a five-month internship at WhizAI in 2020, where she focused on AI and NLP services. Throughout her career, she has developed domain-specific and generic custom parts of speech taggers and disambiguators, showcasing her proficiency in NLP and machine learning.
Technical Skills
Megha Sinha is proficient in various programming libraries and tools essential for NLP tasks. She utilizes libraries such as NLTK, Spacy, Sci-kit-learn, and Stanford Core NLP. Additionally, she employs the JAVA WordNet library and Java WordNet Interface for semantic analysis. Her experience extends to database management with Postgres and deployment tools like Docker and Kubernetes, enhancing her capability in handling complex linguistic challenges.