About
Highly motivated Computer Science Engineering student with a strong foundation in machine learning, data analysis, and robust data pipeline development. Proven ability to drive significant improvements in model accuracy and data processing efficiency through practical application of advanced ML techniques and MLOps frameworks. Eager to leverage analytical prowess and technical skills to solve complex challenges in data science and AI roles.
Work
Bangalore, Karnataka, India
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Summary
As a Data Analyst Intern, Dev Bansal optimized traffic flow analysis and enhanced ML model performance for urban planning simulations.
Highlights
Achieved a 15% accuracy uplift in traffic flow analysis by deploying a custom YOLO model, trained on over 50,000 images, to inform data-driven urban planning simulations.
Increased ML model accuracy by 15 points, reaching 96%, through establishing an MLOps framework in MLFlow to track over 50 experimental runs for continuous fine-tuning.
Engineered a high-throughput streaming solution with Apache Kafka, processing over 200 GB of data daily at 1,000+ events/sec and reducing data latency by 30%.
Languages
English
Hindi
Skills
Technical Skills
Exploratory Data Analysis (EDA), Statistical Analysis, A/B Testing, Data Visualization, MLOps.
Languages & Libraries
Python, Pandas, NumPy, Java, TensorFlow, Scikit-learn, XG Boost, Apache Kafka.
Databases
SQL, MySQL, MongoDB.
BI Tools
Power BI, Excel.
Developer Tools
Git, GitHub, Streamlit, Flask, MLFlow.