Sourav Karmakar

PlayStore App Review Analysis

Analyzed Play Store app reviews to understand consumer behavior and app category trends.

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Bike Sharing Demand

Predicted bike sharing demand with R² 0.909, MAE 2.6 using Gradient Boost & regression models.

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Airline Referral Prediction

Achieved 95.7% accuracy in predicting airline referrals using Logistic Regression, XGBoost, RF models.

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Netflix Movies and TV Shows Clustering

Built a recommendation engine with 90%+ accuracy using K-means & DBSCAN clustering.

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Langchain App

Developed AI-driven applications using Langchain for advanced functionality.

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Fake News Detection

Implemented machine learning models to detect fake news with high accuracy.

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Stock Market Prediction

Achieved 93% intraday accuracy using ANN, CNN, LSTM models.

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Building execution engines, backtesting systems & AI-driven stock market solutions with passion and purpose.

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About Me

I am a Software Developer passionate about merging AI, Stock Market, and Software Engineering. Currently at Levitas, I have built multi-stock execution engines and backtesting systems. Recognized for achieving 93% accuracy in stock predictions, I aim to grow as a FinTech innovator, driven by a deep curiosity and commitment to creating impactful solutions that resonate with real-world challenges.

Resume

Professional Experience

Software Developer – Levitas

Feb 2025 – Present

Developed multi-client, multi-stock Cash Execution Engine
Built Cash & Options Backtesting Engines
Designed automation-driven stock market solutions

Education

MBA – Data Science & AI with SAS

Chandigarh University, 08/2023 – 08/2025

SAS tools | Deep Learning & Neural Networks | NLP | Python for Data Science

Full Stack Data Science

Almabetter, 07/2022 – 01/2023

Star Performer | Completed 4 projects improving ML accuracy >90%

BBA Graduate

IITTM Bhubaneswar, 07/2019 – 05/2022, CGPA 8.32

Travel Data Analysis | Statistics for Business

Projects

PlayStore App Review Analysis

Analyzed Play Store app reviews to understand consumer behavior and app category trends.

View on GitHub

Bike Sharing Demand

Predicted bike sharing demand with R² 0.909, MAE 2.6 using Gradient Boost & regression models.

View on GitHub

Airline Referral Prediction

Achieved 95.7% accuracy in predicting airline referrals using Logistic Regression, XGBoost, RF models.

View on GitHub

Netflix Movies and TV Shows Clustering

Built a recommendation engine with 90%+ accuracy using K-means & DBSCAN clustering.

View on GitHub

Langchain App

Developed AI-driven applications using Langchain for advanced functionality.

View on GitHub

Fake News Detection

Implemented machine learning models to detect fake news with high accuracy.

View on GitHub

Stock Market Prediction

Achieved 93% intraday accuracy using ANN, CNN, LSTM models.

View on GitHub

Publications & Book

Seoul Bike Sharing

Springer Nature (2024)

Big Data for Android Apps

Data Science & Management (2024)

Bike Sharing Demand

Routledge (2024)

Neurolink (Book)

Lambert Publication, Germany (2024)

Achievements

Hackathon: 93% accuracy in stock predictions (2024)
CU Project Expo: 3rd rank (2024)
SAS Visual Analytics – Global Certification

Contact

Email: karmakarsourav2024@gmail.com
LinkedIn: linkedin.com/in/sourav-karmakar
GitHub: github.com/souravkarma
Portfolio: amiai.in