About

Rahul Nenavath is a highly skilled Data Scientist with over 2 years of experience in building, deploying, and maintaining ML & DL solutions for NLP and CV use cases in startup environments. He is currently working as a Data Scientist at Twimbit, where he leads the AI and Data team responsible for handling Platform's Search & Personalisation, Product Analytics, and ETL Pipelines. Rahul has mentored two interns for Data Science roles for 3 months each and has made significant contributions to the company. Rahul has an M Tech degree in Computer Engineering from the Indian Institute of Information Technology, Design, and Manufacturing, Kancheepuram (IIITDM Kancheepuram), Chennai. He has published research work in high impact International Scientific Journal and has a right blend of research and software engineering experience. Rahul is looking forward to solving challenging problems in the data domain. In his current role, Rahul has updated the record structure in the search engine index (Algolia Index) to improve Search Query Response time by 63%. He has reduced the average query response time from 11 ms to 4ms and enabled Named Entities and Keyword based search using Spacy Transformers and KeyBert packages. Rahul has facilitated content ranking via Flesch's Reading Ease score to prioritize articles that are easy to read and maintains Search Engine configuration and reports search analytics like top searches, CTR, Query Response Time, and Click Position. Rahul has tracked user behavior on the platform using Heap Analytics to understand user sessions, conversions, onboarding flow, features often used & often not used, and active users based on time periods. He has conducted internal sessions to cross teams for the adoption of data dashboards for analytics. Rahul has also built data pipelines to extract content from article URLs and index them onto the platform and developed custom web scrapers to scrape data from various research sources (article links). He has built and maintained staging & production environments for the pipeline and used Github Actions for CI/CD workload. Rahul has worked as an Artificial Intelligence Engineer Intern at Cloudsek, where he developed and trained Character-based, Bi-Directional GRU Siamese Model & CNN Model to detect phishing domain names. He has improved phishing domain name detection accuracy by 40%, achieving an F-1 score of 97 % on the test set. Rahul has also worked on building and deploying HR and G/Tech Chatbots at Hexagon Capability Center India. R