Livith Muthanna M A

Artificial Intelligence & Data Science Engineer

Bengaluru, Karnataka, India

@livith_muthanna_m_a

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About

Artificial Intelligence & Data Science Engineer with hands-on experience in data analytics, Python-based machine learning, and GenAI application development. Proven ability to collect, clean, and analyze datasets, build ML models, and communicate insights through Power BI and Tableau dashboards.

Experience

Android App Development using GenAI Intern

Mindmatrix · Bengaluru, Karnataka, India

Feb 2026 – May 2026

Developed AI-powered Android applications integrating RAG frameworks. Implemented semantic search and agentic solutions using LangChain for intelligent data retrieval workflows. Collaborated with cross-functional teams to design, test, and document GenAI-driven features.
Data Analytics Intern

Jyesta Corporate Entity · Bengaluru, Karnataka, India

Oct 2025 – Dec 2025

Collected, cleaned, and preprocessed large datasets to ensure data quality and integrity for analysis pipelines. Conducted exploratory data analysis (EDA) to uncover trends, patterns, and actionable business insights. Built and evaluated machine learning models (Logistic Regression, Decision Trees) using Python and Scikit-learn.

Education

2026

Bachelor of Engineering

Coorg Institute of Technology, Ponnampet, Karnataka

Awarded by Visvesvaraya Technological University

Artificial Intelligence and Data Science · Jul 2022 – May 2026

Artificial Intelligence and Data Science · Jul 2022 – May 2026
2022

senior secondary school completion certificate

Cauvery PU College

2021 – 2022

2021 – 2022
2020

Secondary School Leaving Certificate

Roots Educational Trust

2019 – 2020

2019 – 2020

Skills

6 to 12 months

SQL Git Python Data Science Data Analytics Microsoft Excel Exploratory Data Analysis Generative AI (ChatGPT, Copilot, Gemini)

3 to 6 months

C NumPy Pandas Matplotlib Deep Learning Semantic Search Android development

<3 months

Java LangChain Statistics scikit-learn Decision Trees Linear Regression Hypothesis Testing Agentic AI Systems Regression Analysis Logistic Regression ( in progress )

Tools / apps / platforms

1 to 2 years

GitHub Visual Studio Code

6 to 12 months

Git Microsoft Excel Jupyter Notebook Microsoft Power BI

3 to 6 months

MySQL MongoDB Firebase Android Studio

<3 months

Tableau Antigravity Raspberry Pi

Languages

Fluent

Hindi Speak English Speak Kannada Speak

Basic

Tamil Speak

Projects

Jenu Gumpu Android App ↗

Kotlin, Jetpack Compose, Firebase, Gen AI, MVVM, Kotlin Coroutines & Flow,

Jenu-Gumpu is a digital collective for honey producers. It tracks harvest logs and monitors live market prices. Automated grading and AI insights optimize production quality. The app supports English and Kannada for regional empowerment. Built with Kotlin and Firebase, it provides forest guardians with modern data tools.
Interview Agent ↗

Python, Gen AI, React, Browser Web Speech API

AI-powered Technical Interview Agent with multi-turn role simulation, real-time rubric scoring, speech-to-text dictation, and executive hiring reports.
Resume Screening Agent ↗

Python, scikit-learn, Git, VS Code, pypdf, python-docx

A Python-based Resume Screening Agent that parses resumes (PDF/DOCX/text), extracts structured candidate data, scores and ranks candidates against a job description using transparent weighted logic, flags incomplete resumes for manual review.
Ecommerce Sales Analytics ↗

Python, SQL, Power BI, Pandas, Matplotlib, Seaborn

Developed an end-to-end data analytics solution by cleaning, transforming and analyzing e-commerce sales data to uncover actionable business insights. Built an interactive Power BI dashboard featuring KPI cards, trend analysis, geographic sales mapping, customer segmentation and product performance visualizations. Performed exploratory data analysis using Python and SQL to evaluate sales trends, regional performance, profitability and customer purchasing behavior.
AI Smart Glasses for the Visually Impaired ↗

Machine Learning, Computer Vision, Raspberry Pi, YOLOv3, LBPH, Python

Engineered an offline wearable AI device on Raspberry Pi 5 providing reliable spatial awareness for the visually impaired. Applied YOLOv3 and LBPH models for rapid object detection and accurate facial recognition. Implemented fully local processing pipelines to ensure immediate, offline environmental feedback.
Driver Drowsiness Detection System ↗

Python, OpenCV, Dlib, Computer Vision, Machine Learning, SVM

Engineered a real-time, non-intrusive computer vision system to prevent accidents by continuously monitoring driver fatigue. Applied OpenCV, Dlib, and Haar cascades with 68-point facial landmarks to calculate the Eye Aspect Ratio (EAR). Implemented an audio-visual alert pipeline triggered by prolonged eye closure, achieving an 80% detection accuracy.

Courses & certifications

100 Days of Code – Python Pro Bootcamp · Udemy · 2026
Deep Learning with Python · Infosys Springboard · 2025
Power BI · Infosys Springboard · 2025
SAS Business Analytics for Beginners · Infosys Springboard · 2025

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