Jeevan Surya Jalli

I turn data into insights and ideas into useful digital experiences.

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BASED IN VISAKHAPATNAM, IN

FOCUS DATA × SOFTWARE

01 / 06 PROFILE

STUDENT AI & DATA SCIENCE

CGPA 8.4 / 10

STACK SQL · PY · BI

ABOUT ME

More than just data.

I'm an AI & Data Science undergraduate interested in building things that are useful, measurable, and well designed.

My current work revolves around SQL, Python, Power BI, data analysis, machine learning, and frontend development. I enjoy understanding how systems work and turning that understanding into practical solutions.

01 3+ PROJECTS SHIPPED

02 5+ TECH STACKS

03 2028 GRADUATION

04 2+ YEARS CODING

SELECTED WORK

Things I've built.

Machine learning, analytics, and data-driven projects built to solve practical problems.

Eillish Neural Architecture AI platform preview

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AI PLATFORM · AST VECTORIZATION · AGENTIC RAG

Eillish Neural Architecture

Problem: Developers and engineering teams struggle to navigate, trace dependencies, and reason over distributed codebases, multi-language abstract syntax trees (ASTs), and fragmented technical documentation.

Solution: Built an AI-powered neural knowledge system that vectorizes codebases, preserves AST semantic boundaries, and uses agentic RAG to query and reason over complex code dependencies with machine precision.

ReactTypeScriptVector RAGAST ParsingPythonVercel

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NLP · MACHINE LEARNING · EXPLAINABLE AI

Fake Job Posting Detection

Problem: Job seekers lose time and face risks from fraudulent job postings that collect personal data or demand upfront payments.

Solution: Built an NLP-powered ML system that detects fake job postings with 92% accuracy, using TF-IDF, engineered features, and explainable predictions to help users stay safe.

PythonNLPScikit-learnTF-IDFModel Evaluation

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MACHINE LEARNING · DATA ANALYSIS

Travel Analysis

Problem: Travel companies struggle to predict customer booking patterns and optimize their offerings.

Solution: Applied classification models (Logistic Regression, Decision Tree, Random Forest) to analyze travel data, identify key booking predictors, and uncover actionable patterns for business decisions.

PythonEDALogistic RegressionDecision TreeRandom Forest

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