Venkataramana Patchipulusu
About Venkataramana Patchipulusu
Venkataramana Patchipulusu is a Senior Data Scientist at AppOrchid Inc, with extensive experience in machine learning and natural language processing. He has held various roles in software engineering and data science across multiple companies, primarily in India, before relocating to the United States.
Work at App Orchid
Currently, Venkataramana Patchipulusu serves as a Senior Data Scientist at AppOrchid Inc, a position he has held since 2018. In this role, he is responsible for guiding and overseeing the data science team, providing strategic directions to achieve long-term goals. He participates in both onsite and offshore coordination to ensure project deliverables are met. His work involves converting business issues into data science problems and conducting feasibility assessments.
Previous Experience in Data Science and Software Engineering
Before joining AppOrchid, Venkataramana worked at several organizations in various roles. He was a Module Lead at Mindtree from 2014 to 2016, where he contributed to project management and team leadership. Prior to that, he served as a Senior Software Engineer at Kaara Info Systems from 2016 to 2018 and at Tech Mahindra from 2010 to 2014. Additionally, he gained experience in big data analytics while working at the International School of Engineering in 2015.
Education and Expertise
Venkataramana holds a Bachelor’s Degree in Computer Science from B V C Engineering College, where he studied from 2005 to 2009. His expertise includes using TensorFlow, PySpark, and Keras for building machine learning models. He also has a strong background in natural language processing, utilizing libraries such as NLTK. His skills enable him to design and build mathematical and statistical models that enhance data-driven business decisions.
Technical Skills and Contributions
Venkataramana Patchipulusu has developed proof of concept prototype algorithms for feasibility studies. His work involves designing and building models that address complex data science challenges. He has a proven ability to convert business issues into data science problems, showcasing his analytical skills and technical knowledge in the field.