I'm passionate about creating innovative solutions through code and data. With expertise in both software engineering and data science, I build applications that make a difference.
Hello! I'm Venkat, a passionate Software Engineer and Data Scientist with a strong foundation in building innovative applications and deriving insights from data.
I specialize in full-stack development, machine learning, and data analysis. My journey in tech has equipped me with a diverse skill set that allows me to approach problems from multiple angles and develop comprehensive solutions.
I'm constantly learning and exploring new technologies to stay at the forefront of the rapidly evolving tech landscape. My goal is to leverage technology to create impactful solutions that address real-world challenges.
When I'm not coding, you can find me exploring new hiking trails, reading about the latest tech trends, or experimenting with new recipes in the kitchen.
My professional journey blends software engineering and data science expertise, allowing me to approach problems with a multidisciplinary perspective and deliver innovative solutions.
Developed ETL pipelines, built GPT-4-powered RAG systems for NER extraction, and created sentiment analytics plugins using microservices architecture for real-time investor insights.
Developed document management systems, engineered cost-saving workflows, built data validation frameworks, and architected dynamic layout engines while implementing data analytics solutions.
Optimized SQL procedures, developed forecasting tools, and built Node.js-Angular applications for admin settings and config management with integrated data visualization.
Developed a personalized nutrition and exercise recommendation system using LLMs to parse user history and biometric data, combining ML expertise with full-stack development.
Built an AI-powered code review system using Mistral-7B, fine-tuned for pull request analysis and integrated into CI pipeline, showcasing both ML and software engineering skills.
Developed an IoT-based spine diagnostic system and built machine learning models for spine condition classification, achieving an F1 score of 0.98 in this patented study.
(206) 518-8678
Boston, MA