👋  Open to Opportunities

Yegireddy Chandravamsi
Karthik

MBA candidate (IT & Finance) × B.Tech AI & Data Science — bridging machine learning, FinTech analytics, and business strategy to turn complex data into decisions that matter.

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Where Finance Meets Intelligence

I'm an MBA candidate specializing in IT & Finance at ICFAI University, with a B.Tech in Artificial Intelligence and Data Science from Vardhaman College of Engineering (JNTUH).

I combine business analytics, financial modelling, and AI/ML to solve data-driven problems — from credit risk and inventory demand modelling to phishing detection and GenAI pipelines.

My work spans FinTech (credit risk, expected loss), healthcare analytics (Apollo Pharmacies), and cybersecurity (published research). I'm actively seeking roles where technology, finance, and strategy intersect.

8.28
B.Tech CGPA
3
Internships
1
Research Paper
12+
Certifications
🧑‍💻

Skills & Technologies

A curated toolkit spanning ML engineering, cloud platforms, financial analytics, and full-stack data pipelines.

🤖 Machine Learning / AI
XGBoostRandom ForestLogistic RegressionSHAPFeature EngineeringGradient BoostingDecision TreesNLPLLMsRAGPrompt EngineeringEncoder-Decoder
🐍 Languages & Libraries
PythonRJavaCSQLNumPyPandasMatplotlibScikit-learnStreamlit
☁️ Cloud & Data Platforms
Google Cloud PlatformBigQuery MLVertex AIAWSMicrosoft AzureKubernetes
💹 Finance & Business Analytics
Credit Risk ModellingProbability of DefaultExpected Loss (PD×LGD×EAD)Financial AnalysisInventory Demand (ROQ/ROL)IQVIA Market Analytics

Featured Projects

End-to-end systems built with production-grade engineering practices — from data ingestion to interactive dashboards.

01 / FinTech · Credit Risk
Credit Risk & Expected Loss Analytics Platform
End-to-end PD modelling framework on ~890,000 historical LendingClub loans. Applied SHAP TreeExplainer to surface top risk drivers (int_rate, term, dti) and built a 5-page Streamlit dashboard for portfolio monitoring, risk segmentation, model evaluation, and individual loan assessment with live Expected Loss analytics (EL = PD × LGD × EAD). Decision threshold selected on validation set; imputer fitted only on training data — no evaluation leakage.
ROC-AUC 0.789
PR-AUC 0.577
Loans 890k
EL Analytics PD×LGD×EAD
PythonXGBoostSHAPStreamlitLogistic RegressionRandom ForestSklearn PipelineFinTech
02 / Cybersecurity · Research
📄 Published — ICPCSN 2024
Phishing URL Detection using Machine Learning
ML-based phishing URL classifier using 87 structural and lexical URL features — no page content or DNS lookups required. Benchmarked 9 ML models; co-authored and presented research paper at an international conference.
Accuracy 97.4%
Best Model Gradient Boosting
Models 9 Benchmarked
PythonXGBoostGradient BoostingCybersecurityURL AnalysisResearch

Work Experience

Real-world impact across pharma analytics, web development, and data science.

Analyst Intern
Apollo Pharmacies Limited
Feb 2026 – May 2026 · 3 months
  • Analyzed product performance vs IQVIA market trends; identified high-performing and underperforming SKUs and recommended areas of business focus
  • Built a RAG pipeline by scraping and processing annual reports & investor presentations of Indian pharma companies for future insight extraction
  • Developed a data-driven inventory model (ROQ/ROL) for generic products across 100 top Hyderabad stores using sales patterns, bill counts, seasonality, and demand trends
  • Designed a new-product launch framework recommending optimal stores, initial stock allocation, reorder levels, and reorder quantities
Web Developer Intern
Elbert Technologies
Aug 2024 – Nov 2024 · 4 months
  • Developed responsive web pages using HTML, CSS, and JavaScript
  • Collaborated on UI/UX implementation for client projects
Data Science Intern
Cognifyz Technologies
Nov 2023 – Dec 2023 · 2 months
  • Performed data cleaning and exploratory data analysis on restaurant dataset
  • Built and compared RandomForest and Linear Regression models for prediction tasks
  • Created data visualizations to communicate insights to stakeholders

Education

Strong academic foundation combining business intelligence with engineering expertise.

2025 – 2027
Master of Business Administration (MBA)
🎓 ICFAI University, Hyderabad
Specialization: IT & Finance
CGPA: 8.25 / 10
2021 – 2025
B.Tech — Artificial Intelligence & Data Science
🎓 Vardhaman College of Engineering
Affiliated to JNTUH, Hyderabad
CGPA: 8.28 / 10
2019 – 2021
Intermediate — Maths, Physics & Chemistry
🏫 Sri Chaitanya Junior College
Telangana State Board
97.8%
2019
High School
🏫 Rainbow High School
CBSE Board
92.8%

Certifications

Continuous learning across cloud, AI, finance, and security domains.

💹
ChatGPT AI for Finance Professionals
Udemy
📊
The Complete Financial Analyst Course
Udemy
☁️
Generative AI Explorer — Vertex AI
Google Cloud
🧠
Introduction to Large Language Models
Google Cloud
🔁
Encoder-Decoder Architecture
Google Cloud
⚖️
Responsible AI with Google Cloud
Google Cloud
🗄️
BigQuery for Machine Learning
Google Cloud
🤖
Create ML Models with BigQuery ML
Google Cloud
🔧
Engineer Data in Google Cloud
Google Cloud
💬
GenAI: Prompt Engineering
Google Cloud
⚙️
Deploy Kubernetes on Google Cloud
Google Cloud
🔐
Ethical Hacking Essentials
EC-Council

Research & Achievements

RESEARCH PAPER · PUBLISHED
Securing the Web Using URL-Based Analysis and Machine Learning Algorithms
📍 ICPCSN 2024 🏛️ RP Sarathy Institute of Technology 📅 May 14–16, 2025
Co-authored and presented at the 5th International Conference on Pervasive Computing and Social Networking. The paper proposes an ML-based URL classification system achieving 97.4% accuracy using 87 structural and lexical URL features with Gradient Boosting.
LEADERSHIP & INITIATIVES
Full-Stack Development Workshop Coordinator
🏫 Vardhaman College of Engineering 🤝 Neoteric Technologies 📅 Oct 2024
Facilitated collaboration between Neoteric Technologies and Vardhaman College of Engineering — coordinating logistics, scheduling, and communications to successfully conduct a Full-Stack Development Workshop for students.

Let's Connect

Available for opportunities — actively looking

I'm seeking analytical, ML, and strategy roles where technology meets business. Whether it's a job opportunity, internship, collaboration, or just a chat about data — reach out!

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