Devam Sanjay Sheth

San Jose, CA – ***** ad2vce@r.postjobfree.com +1-408-***-****

linkedin.com/devam-sheth github.com/devamsheth0806 EDUCATION

M.S. in Data Science: Aug 2023 – Present

San Jose State University, California, US CGPA: 3.8/4.0 Focus areas: Cluster Analysis, Web Intelligence, Statistical and Machine Learning Classifications, Probability Theory B.Tech. in Computer Science and Engineering: Jul 2017 – Jun 2021 Vellore Institute of Technology, Tamil Nadu, India CGPA: 4.0/4.0 Focus areas: Artificial Intelligence, Machine Learning, Data Visualization, Data Mining, Web Mining, Statistics SKILLS

Languages: Python, Java, SQL, JavaScript, R, Scala, C, C++ Data Science: Machine learning, Deep Learning, Natural Language Processing, Neural Networks, Sci-kit Learn, Tensorflow, PyTorch, Keras, Pandas, Matplotlib, Tableau, Plotly, Numpy Big Data and Cloud: Apache Spark, Apache Hadoop, Apache Kafka, Azure Cloud, Google Cloud, Kubernetes Other: Airflow, Spring Boot, Spring Batch, Zeppelin, ReactJS, OpenCV, Git, Agile, JUnit, Jenkins, CI/CD WORK EXPERIENCE

Software Engineer at Société Générale Global Solution Centre (Bengaluru, India) Jul 2021 – Jul 2023

• Led Big Data initiatives using Apache Spark enhancing ELT data migration to Azure cloud for improved analytics

• Optimized ELT process using Spark on Azure Kubernetes reducing the cost and saving time by 40 hours per month

• Automated CI/CD of data processing pipeline with the help of Jenkins and Airflow, reducing manual effort by 70% Intern at Société Générale Global Solution Centre (Bengaluru, India) Jan 2021 – Jun 2021

• Engineered data-driven UI widget on company dashboard using Preact with Typescript enhancing user interaction

• Automated API monitoring data consolidation with Python improving data integrity in Elastic Search

• Optimized Python scripts for accurate data extraction from Excel sheets, resolving 90% of the issues and improving data quality

Summer Intern at L&T Technology Services Pvt. Ltd. (Vadodara, India) May 2019 – Jun 2019

• Developed an internal portal for efficient data management using PHP and MSSQL enhancing workflow

• Integrated LDAP-based authentication for SSO sign-in to improve application security and user access control PROJECTS

Keratoconus Stage Detection by Supervised Learning Algorithms Jan 2020 – Jun 2020

• Devised two supervised machine-learning models for the classifying stage of the disease using SVM and Deep Neural Network models with 96.2% and 99.5% accuracy, respectively

• Extracted key performance metrics from the data of more than 2,000 patients by decision tree classifier 7-Point Checklist Skin Infection Identification and Classification Algorithms Comparative Analysis Jan 2020 – Jun 2020

• Conducted comparative analysis of machine-learning classifier for validating effective skin infection identification

• Used CNN for feature extraction from images along with Scikit-learn for different ML models development Smart Summarizer Apr 2020 – Jul 2020

• Developed an NLP-based Python application summarizing content through user-provided queries using NLTK and Gensim

• Containerized with Docker to improve scalability, deployment, and availability Covid19 Dashboard Jul 2020 – Oct 2020

• Designed a dynamic COVID-19 dashboard to visualize data using Flask, integrating Plotly for graphs and MapBox for real- time visualization of global case data

CERTIFICATIONS

Coursera: Cloud Computing with Google Cloud (June, 2020), Google Data Analytics (December, 2023) Data Science: DL0320EN: Applied Deep Learning Capstone Project (April, 2020) Microsoft-certified: Azure Fundamentals (AZ-900), Azure Data Fundamentals (DP-900), Azure Administrator Associate (AZ- 104), Azure Data Engineer Associate (DP-203)

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