Data Science Machine Learning

Shambhavi Madhukar Puttane Email: ***********@*****.***

www.linkedin.com/in/shambhavi-puttane Mobile: 442-***-**** Education

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Arizona State University Arizona, AZ

Master of Science in Data Science, Analytics and Engineering; Anticipated GPA: 4.0 Aug. 2024 – May. 2026

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PES University Bangalore, India

Bachelor of Technology in Computer Science; GPA: 3.68 (9.06/10.0) Aug. 2019 – Aug. 2022 Experience

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Hewlett Packard Enterprise (Aruba Networking) Bangalore, India Cloud Engineer Jan. 2023 – Aug. 2024

– Enhanced Aruba’s SD-Branch solution: Developed features like traceroute and dynamic DNS, improving network reliability by 30%.

– Automated Deployment: Utilized Docker, Kubernetes, and YANG models to automate scalable infrastructure.

– Workflow Optimization: Automated REST API and GraphQL scripts, increasing productivity by 50%.

– Testing and Quality Assurance: Reduced critical bugs by 95% using JIRA, Selenium, and Cypress for manual and automated testing.

– Agile Methodologies: Streamlined processes, reducing project delivery time by 20%.

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Indegene Limited Bangalore, India

Data Engineer Intern June 2022 – Aug. 2022

– Data Migration: Ensured 100% data integrity during migrations from SFTP, Azure, and SFMC platforms,improving data reliability and system performance.

– ETL and Big Data Processing: Executed data pipelines using Python, Spark, and Hadoop, reducing processing time by 30% and enabling efficient data visualization for stakeholders.

– Data Warehousing: Optimized AWS S3 and Redshift workflows with PySpark, improving transfer efficiency by 25%and enhancing database interactions.

Projects

• US Mass Shooting Data Analysis: Conducted statistical analysis on behavioral, demographic, trauma, weapon, and motivational datasets to study mass shooting patterns. Applied preprocessing (binary encoding, normalization), descriptive statistics, heatmaps, regression diagnostics, and hypothesis testing (ANOVA, chi-square, logistic and linear regressions) to derive actionable insights.

• AI/NLP 3D Interior Modeling: Designed a 3D interior room model by integrating NLP techniques (BERT) with Deep learning frameworks (TensorFlow). Graph Convolutional Networks (GCN) was applied to parse user-generated text, and Generative Adversarial Networks (GANs) were used for interior texture generation. Executed AI training and tuning for model optimization, utilizing advanced NLP techniques (BERT, GCN) and integrated GPU resources to benchmark and fine-tune model performance.

• Threat Detection with Explainable AI: Built a machine learning model using scikit-learn to classify network traffic, improving prediction accuracy by 20 % than base model and implemented automated incident response system that uses XAI to explain its decision-making process using AI framework (Tenserflow and Hugging Face).

• E-commerce Web Development: Built a full-stack e-commerce application using the MERN stack (MongoDB, Express.js, React.js, Node.js) with features like login, cart, and checkout functionality.

• Workplace Data Analysis: Developed machine learning models to analyze data on workplace mental health trends where predictive analytics models were applied, including Regression, Decision Trees, SVM, KNN and Adaboost Classifier to forecast workplace mental health trends and provide actionable insights for organizational well-being strategies

• AI Chatbot Development: Designed an AI chatbot using Transfer Learning and LSTM in Python, constructing an encoder-decoder architecture for effective conversation modeling.

Coursework

• Big Data Analysis, Machine Learning, Advanced Python Programming, Distributed Database Systems, Image Processing, Network Mining Analysis, Principles of Data Science, Information Assurance and Security, Web Development. Skills

• Languages: Python, SQL, R, PySpark, JavaScript, Java, C++, PostgreSQL, MongoDB

• Technologies: ETL Pipelines, Big Data Processing, Data Warehousing, AWS (S3, Redshift), Spark, Hadoop, Tableau, Data Visualization, Statistical Analysis, Computer Vision, LLMs, Data Visualization, Spark, Hadoop, Docker, Kubernetes, TensorFlow, Pandas, Machine Learning, AI, NLP.

• Tools: Git, JIRA, MS Office, Selenium, AWS S3, AWS Redshift

• Soft Skills: Communication, Teamwork, Problem-Solving, Presentation, Critical Thinking, Collaboration. Publication

Kulkarni, R. P., & Puttane, S. M. (2024). Framework for Home Layout Design by Semantic Parsing of Text. Advances in Computational Intelligence and Its Applications, 195.