Data Engineer Science

POOJITA KAJA

**** ***** **, ***********, ******* 32304

448-***-**** ***********@*****.***

Education

Florida State University Aug 2023 – Present

Master’s in Interdisciplinary Data Science GPA: 3.8/4.0 SRM University Jun 2019 – May 2023

Bachelor of Technology in Electronics and Communication Engineering GPA: 8.6/10 Work Experience

Freelance Data Engineer Dec 2024 – Present

Independent Data Analysis Project

• Analyzed truck sales data using Excel, identifying seasonal demand patterns and anomalies, which improved forecasting accuracy by 15%.

• Designed over 10 data visualizations to communicate insights, enabling data-driven strategic adjustments.

• Implemented strategies that led to a 10% increase in sales performance within three months.

• Enhanced overall data quality by implementing targeted strategies that identified the three primary issues causing inaccuracies, ultimately leading to more reliable analyses. Key Projects

Skin Cancer Detection Using Deep Learning and GANs

• Composed a book chapter featured in Springer that evaluates the long-term benefits of cloud computing; this analysis reached an audience of over 500 professionals, sparking discussions in corporate strategy meetings.(Springer Link).

• Integrated SRGAN and DCGAN models to generate high-resolution synthetic medical images, increasing dataset size by 150%.

• Improved cancer classification model accuracy by 10% through advanced data augmentation techniques. Face Mask Detection Using Computer Vision

• Developed and patented the ”System and Method for Detecting a Face Mask.” Patent Link.

• Engineered a deep learning-based mask detection system using OpenCV, TensorFlow, and Keras, achieving 90% classification accuracy with the MobileNetV2 architecture.

• Enhanced model performance, reducing inference time by 25% to enhance real-time compliance feedback.

• Deployed the system in a university environment, automating real-time feedback for over 1,000 users, which resulted in a 30% increase in adherence to safety protocols Fire Detection System Using Deep Learning

• Built an AI-powered fire detection system with real-time monitoring using TensorFlow and Keras.

• Refined CNN architecture, improving feature extraction and efficiency achieving a 90% detection accuracy and reducing false alarms by 20%.

• Configured the system on AWS Lambda for scalable real-time processing, improving response time by 35%.

• Conducted real-world testing in a simulated environment, demonstrating a 25% improvement in fire detection speed.

• Engineered a sophisticated system with IoT thermal cameras and edge computing, achieving real-time detection that resulted in first responders receiving alerts within an average of 5 seconds post-incident, ensuring swift action.

Technical Skills

Programming: Python, SQL(PostgreSQL, Oracle SQL), R, C++ Frameworks: TensorFlow, Keras, Scikit-learn, PySpark Tools: AWS, Apache Airflow, Kafka, Snowflake

Data Visualization Tools: Power BI, Tableau, Docker Data Engineering: ETL Pipelines, Data Warehousing, Big Data Processing, Data Cleaning, API Integration https://www.linkedin.com/in/poojitakaja/

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