Jaswanth Aalla Balaji
AI Software Engineer | Data Scientist | RAG | Master’s Data Science @University at Buffalo | Master’s Software Engineering @Vellore Institute of Technology
- Role
- Data Analyst at Community Dreams Foundation
- Location
- Buffalo, NY, US
- LinkedIn followers
- 500 followers
About Jaswanth Aalla Balaji
Currently pursuing a Master\'s of Professional Studies in Data Sciences and Applications at the University at Buffalo, with expected graduation in December 2025. Previous academic achievements include completing a Master of Technology in Computer Software Engineering at Vellore Institute of Technology in 2024. Certifications in data analytics and software design complement a strong foundation in Python, machine learning algorithms, and cybersecurity. Conducted research on deep learning–based medical diagnosis at Vellore Institute of Technology, leading to a publication in the International Conference on Artificial Intelligence and Human Interaction. Designed convolutional neural network architectures and optimized predictive models for multidisease diagnosis. Passionate about applying technical expertise to solve real-world challenges and contributing to innovative data science projects.
Experience
Data Analyst
Feb 2026 — Present · Buffalo, NY, US
Data Analyst at Community Dream Foundation, working at the intersection of energy infrastructure and modern data engineering. Contributing to an AI-powered interactive grid visualization platform built on microservices architecture, designed to bring real-time intelligence to the US power grid.My core responsibility is building clean, production-ready datasets from raw multi-source grid data processing 7.9M+ records across electricity pricing, transmission constraints, and generation capacity sourced from NYISO, FERC, and EIA. Engineered end-to-end data quality pipelines that reduced data inconsistencies by over 98%, flagging and resolving complex real-world edge cases including market anomalies, temporal discontinuities, and DST-induced duplicate records ensuring zero data loss throughout the process.These validated datasets directly feed the platform\'s machine learning models and geospatial visualization layer, accelerating the analytics team\'s time-to-insight by eliminating manual data correction overhead in downstream sprints.
Education
Vellore Institute of Technology
Master of Technology - MTech
2019 — 2024
University at Buffalo
Master's of Professional Studies in Data Sciences and Applications
2024 — 2025
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