Data Analyst Python

DARSHIT JAGETIYA

San Jose, CA ***** 669-***-**** *******.*****@*****.*** LINKEDIN /in/darshit-jagetiya/ GITHUB /darshitj15 EDUCATION

Master of Science, Data Analytics; GPA - 3.85/4 Expected Dec 2021 San Jose State University, San Jose, CA

Bachelor of Technology, Industrial Engineering; GPA - 8.61/10 May 2019 Pandit Deendayal Petroleum University, Gandhinagar, India EXPERIENCE

Data Analyst (Student Assistant), IT Department, San Jose State University Nov 2020 - Present

• Built interactive visualization dashboards to identify peak concurrent sessions on university servers and analyzed student login data on university applications to maintain efficient utilization of IT resources.

• Maintained databases by making sure of data hygiene and data segmentation for the computing services and automated existing disparate data systems into organized data repositories using Pandas and Regex in Python.

• Provided IT support to students/staff to solve account and device-related issues with excellent communication skills. Python Software Developer (Volunteer), FIPWF LLC, Sacramento, CA May - Oct 2020

• Built automated data pipelines by creating web scrapers with Python collecting rent amounts from multiple data sources using automation tool Selenium and integrated with databases replacing manual data inputting.

• Deployed Restful APIs to auto-upload files on cloud and auto-send email to tenants.

• Integrated all these steps and built an app (frontend and backend – Open Source) to auto-generate invoices and created a file-sharing tool that shares documents with all its customers.

• Programmed a Python visualization tool that delivered dashboards to c-level management by collecting expenses from the database enabling budget analysis of properties. Operations Intern, Ford Motor Company, Ahmedabad, India Jun - Aug 2018

• Increased the efficiency of the engine plant by analyzing the engine plant workload data, designed simulations, and implemented new part supplying models to increase manufacturing capacity.

• Collected and analyzed datasets on new simulation line layout expansion and assisted in conducting comprehensive strategic and justification analyses backed by data visualization with the team TECHNICAL SKILLS

Programming: Python, SQL, R, Hive

Technologies: Jupyter Notebooks, PyCharm, Scikit-Learn, TensorFlow, Pandas, NumPy, MongoDB, MySQL, Tableau, Git, Hadoop, Office365

Coursework: Programming for Data Analysis, Statistics for Data Science, Machine Learning, Deep Learning, Database Management Systems, Data Visualization, Big Data Technologies, Data Mining. ACADEMIC PROJECTS

Movie Recommendation System, SJSU

Designed a Machine Learning movie recommendation system based on 20 million ratings given by 138000 users. Performed Exploratory Data Analysis and developed a Matrix Factorization model using Singular Value Decomposition. Team of 3, Fall 2020)

Sentiment and Similarity Analysis of Movie Reviews, SJSU Created datasets by scraping movie reviews by critics to perform sentiment and similarity analysis. Applied Naive Bayes to get movie ratings by applying sentiment analysis and compared it with actual ratings using confusion matrix. Performed similarity analysis to match the same critics from their own reviews and visualize with word clouds. (Spring 2020) Titanic Survival Prediction (ML model from Scratch - Kaggle Competition), SJSU Built a K-Nearest Neighbors machine learning model from scratch to predict the survival of Titanic passengers. Identified feature dependencies to remove redundancy and applied Random forest, Naïve Bayes, to ensemble the Machine Learning models and took the maximum vote for prediction. (Fall 2020) Dashboard Visualization of Data Science Jobs, SJSU Performed ETL by scraping Data Science job data from indeed using Python to make datasets and extracted features from descriptions. Created a Tableau Dashboard to generate insights on skill requirements, salary estimations, region, and rating of companies for different Data Science roles along with various filters to give user control.

(Team of 4, Fall 2020)

User Engagement Analysis, SJSU

Analyzed the user engagement activity for an enterprise’s data collected for 2 years and determined the reasons for the reduction in user engagement by performing time-series analysis using SQL. Generated multiple visualization charts to analyze the pattern and provided future insights on different data factors using Databricks. (Spring 2020)

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