Thirumurugan Kumar
000
Portfolio · Data Science · AI
Data Science • Analytics • AI • Machine Learning
Designing data-driven systems, analytics solutions, and machine learning pipelines that deliver measurable business impact.
DATA TO DECISION INTELLIGENCE
Transform raw structured data into polished dashboards, insights, and executive-ready recommendations.
PREDICTIVE SYSTEMS
Deliver predictive models and forecasting pipelines that anticipate outcomes and guide strategy.
AI-POWERED APPLICATIONS
Build intelligent applications using NLP, deep learning, and scalable AI infrastructure.
OPERATIONAL ANALYTICS
Deploy data-driven workflows that provide reliable metrics, optimization signals, and business impact.
Overview
I am Thirumurugan Kumar a data scientist and machine learning engineer who transforms complex, messy data into systems that drive real decisions and measurable outcomes.
My work spans the full depth of modern data: precision-engineered Python pipelines, scalable SQL architecture, production-grade ML models, NLP platforms, and deployed APIs. I do not stop at the notebook I build things that run in the real world.
What makes me different is the rare combination of analytical rigour and creative vision. I am also a photographer trained to see light, composition, and narrative in a single frame. That instinct shapes everything from how I design a dashboard to how I tell a data story to an executive audience.
I am confident, curious, and relentlessly structured. I learn fast, adapt faster, and bring both technical depth and clear communication to every team I join.
Currently pursuing my Master's in Data Science and Analytics at EPITA, Paris actively seeking internships where data, intelligence, and impact intersect.
Toolkit
A practical stack for analytics, engineering, and AI delivery.
I design and deliver high-impact data systems by combining analytics, machine learning, and scalable engineering practices.
Write clean, scalable code for analytics workflows, backend APIs, automation, and production-ready data applications.
Turn raw structured data into actionable insights through exploration, KPI tracking, trend analysis, and business-focused interpretation.
Build dashboards and visual narratives that communicate performance clearly and support faster, better decisions.
Develop predictive models for classification, forecasting, and decision-support using practical supervised learning methods.
Design neural network solutions for pattern recognition, sequence modeling, and advanced data representation tasks.
Apply natural language processing techniques to extract meaning, classify text, and enable intelligent language-based systems.
Deploy and manage scalable systems using APIs, containers, and workflow orchestration tools for real-world usage.
Handle data storage, querying, and management using reliable database systems and supporting tools.
A curated set of analytics, machine learning, and AI systems designed to solve real-world problems through data-driven approaches.
Featured case study
End-to-end data analytics solution — from raw retail data to a two-page Power BI executive dashboard — delivering $2.29M revenue insights, KPI tracking, and actionable business recommendations.
Impact
Delivered a complete business analytics system that enables KPI-driven decision-making. Key recommendation: reducing aggressive discounting and refocusing on high-margin segments could meaningfully improve the 12.47% profit margin. The dashboard is directly presentable to business leadership without technical translation.
Featured case study
Production-grade end-to-end ML platform — Apache Airflow pipelines, FastAPI prediction API, Great Expectations data validation, Grafana monitoring, and a Streamlit dashboard — predicting employee attrition at 85–92% accuracy.
Impact
The system replaces manual HR analysis with an automated, always-on prediction platform. It enables proactive retention decisions at scale — identifying at-risk employees before they resign, reducing turnover by an estimated 25–40%, and cutting manual analytics effort by 80%. Every prediction is logged, traceable, and auditable.
Featured case study
Full-stack NLP system using an ensemble of LSTM, GRU, TextCNN, and BERT models combined with live web evidence scraping to classify news credibility with explainable, evidence-backed predictions.
Impact
The platform demonstrates that fake news detection does not have to be a black box. By combining multiple NLP architectures with external evidence, predictions become trustworthy and auditable — suitable for use by fact-checkers, newsrooms, or content moderation teams. The architecture is extensible to real-time social media monitoring.
Featured case study
Production-grade AI resume intelligence platform that analyzes resume-job compatibility using ATS scoring, NLP-based skill extraction, semantic similarity, and recruiter-focused feedback generation.
Impact
Automates resume screening workflows and helps candidates improve ATS alignment, identify missing skills, and generate recruiter-ready job application materials faster.
Featured case study
Graph-based analysis of darknet activity to identify hidden relationships and criminal networks.
Impact
Enabled identification of key actors in networks.
Featured case study
Computer vision system for detecting vehicles and analyzing traffic patterns in real time.
Impact
Improved monitoring efficiency with automation.
A focused progression from software and IT foundations to data science, analytics, machine learning, and production-ready systems.
2024 — 2026
EPITA | Paris, France
Specializing in data science, machine learning, and analytics systems with a focus on building scalable, real-world data-driven solutions.
2020 — 2024
St. Joseph’s College of Engineering | Chennai, India
Developed a strong foundation in computer science, software engineering, and information systems through structured academic training and practical implementation.
2024
NSIC | Mobile Application Development
Designed and delivered Android application features with a focus on performance, usability, and real-world deployment, working closely with design and backend teams.
Download a refined résumé preview that highlights my focus in analytics, ML, and deployed systems, along with selective internship interests.
Résumé preview
Snapshot
I design analytics systems and machine learning solutions that turn complex data into confident business decisions.
Focus areas
Internship interests
Career narrative
I focus on analytics and AI product delivery, creating dashboards, predictive models, and deployed systems that move teams from insight to action.
Highlighted strengths
Reach out to discuss analytics programs, AI product strategy, or data-driven transformation initiatives.
Trusted contact
I’m available for internships, analytics roles, and AI product discussions. Share the project scope, and I’ll respond with clarity and speed.
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