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Data Python

Ashburn, VA, 20147
April 17, 2021

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Shreya S. Gavasane



University of Maryland, Baltimore County, Baltimore, MD GPA: 3.9 Master of Science, Engineering/Industrial Management August 2019 – May 2021 Graduate Certificate, Data Science

Graduate Certificate, Project Management

Maharashtra Institute of Technology, Pune, India

Bachelor of Engineering, Computer Engineering Graduated, June 2018 SKILLS

Programming: C++, Python

Databases: MySQL, MongoDB, Spark Sql

Software Packages: Microsoft Office, Hubspot CRM Tool, Micro Strategy, Asana, Microsoft Project, Tableau, PowerBI, Pyspark Tools: IDP, Jupyter Notebook, SAP Canva, Microsoft Excel (VLOOKUP, pivot tables), Apache Spark, Hadoop OS/Platforms: Windows, Mac OS, Linux


Data Intern, Index Analytics LLC, Maryland, USA September 2020 – Present

Translated business needs to technical specifications; BI designing and development using PowerBI and Tableau.. Collaborated with teams to integrate systems.

Designed visualization with PowerBI to make interactive dashboards and toolkits for internal risk monitoring and business unit insights. Implemented solutions using Agile, Scrum, JIRA, automated tests, and behavior-driven development

Identified and acquired necessary data from multiple sources and extracts, cleans, transforms, and loads data sources to enhance data quality as part of analytics analysis. Cleaned data as part of analysis and then identified and interpreted trends and patterns in datasets to locate influences.

Created scripts to enhance automation within ETL processes, and other business processes - through SQL and Python.

Used data modeling and analysis techniques to discover insights which guided strategic decisions and uncovered optimization opportunities.

Software Engineer Intern, IP Commercialization Labs, Maryland, USA July 2020 – December 2020

Analyzed the data and created the data visualization reports of the given data using Python, MongoDB, and Tableau.

Applied industry and business knowledge to interpret data and developed actionable insights that improved performance

Interpreted data analyzed results using statistical techniques and provided ongoing reports.

Worked on tools and services of AWS. The technology I worked on includes Python, Numpy, Pandas, Sklearn, Seaborn, Matplotlib, and Python-pptx. The databases I worked on include MongoDB. Business Analyst, Uniview Technology Pvt Ltd, Mumbai, India June 2018 – July 2019

Worked closely with peers and stakeholders to organize, access, monitor, and control the evaluated data from a variety of sources; collected new data, connected data types and used existing data creatively to formulate solutions using Python and SQL. Queried the data and provided reports to stakeholders.

Built, developed and maintained data models, reporting systems, data automation systems, dashboards and performance metrics that supported key business decisions.

Created new and enhanced ways of visualizing data sets using Tableau that enabled business decision-making and told compelling stories through dashboards, presentations and business cases.

Performed tasks such as business requirements gathering; documenting current and future state workflows including cross functional interdependencies;

Project Management Intern, D-Vois Communications Pvt Ltd, Mumbai, India June 2017 – Oct 2017

Assisted in project management for an emerging Telecommunications domain.

Established project life cycle and exception plans; broke down development tasks into assignments for team-members

Measured bandwidth usage with time series analysis; created visualizations of usage in Python GPA: 3.2


Premier League Analysis Using Big Data Tools. October – December 2020

Sorted the semi-structured data using MongoDB and integrated the data with Spark SQL and python.

Carried out data extraction, cleaning, data analysis, and operations using Spark (pyspark, SparkSQL, and Map-reduce).

Modeled the data and carried out predictions of the players and teams playing in the league using Neural Networks. Integrated the data (MongoDB, Spark SQL, and Python) with Tableau and created interactive dashboards for storytelling. Technology used - MongoDB, Pandas, PySpark, SparkSQL, Tableau, Python, Neural Networks, and Google Colab Diabetes Readmission Prediction November – December 2020

Predicted if a patient with diabetes will be readmitted to the hospital within 30 days

The data was extracted, cleaned, and analyzed using Python. (Feature Scaling & Engineering and Hyperparameter tuning).

Data was modeled using various machine learning algorithms and predictions were carried out

With the help of results obtained from those machine learning algorithms AUC-ROC and AUC-PR curves were plotted. Technology used – Python, Google Colab, Pandas, Numpy, Logistic Regression, K-Nearest Neighbors, Gaussian Naïve Bayes, Random Forest Classifier, Decision Tree Classifier, Gradient Boosting Classifier, AUC-ROC, and AUC-PR. News Media Bias Visualizer. July – August 2020

Assembled and retrieved the news content using Media Bias dataset, News API, Clear bit API, and Metadata API.

Analyzed the retrieved data using text analysis and sentiment analysis, displayed the media bias of the news sources relative to important topics covered.

Carried out all these tasks using python and ML libraries and frameworks like Scikit-learn. Created visualization using Matplotlib, Seaborn, and Tableau.

Technology used - Google Colab, Python, Numpy, Pandas, Matplotlib, Seaborn, Sentiment Analysis, Scikit-learn, and Tableau.

Identification of Acute Lymphoblastic Leukemia in Microscopic Blood Image Using Image Processing and Machine Learning Algorithms (Published Research Article) December 2017- May 2018

Developed a standalone GUI using PyGTK and web using django for identification. The ALL (Acute Lymphoblastic Leukemia) IDB dataset was used for this project. Feature extraction was carried out using OpenCV. The machine learning algorithms used for classification included FNN, CNN, SVM and KNN Proceedings of 7th International Conference on Advance Computing, Communications and Informatics (ICACCI). September 19-22, 2018, Bangalore, India.

DOI: 10.1109/ICACCI.2018.8554576

URL: Technology used – OpenCV, Python, django, SQL, FNN, CNN, SVM, and KNN. CERTIFICATION

Data Analytics Fundamentals issued by AWS Training and Certifications June 2020 – no expiration date

AWS Fundamentals course in the AWS Machine Learning Scholarship issued by Udacity June 2020 – no expiration date

Python Bootcamp: Go Beginner to Expert in Python 3 issued by Udemy July 2020 – no expiration date

Tableau Training: Master Tableau For Data Science issued by Udemy November 2020 – no expiration date CONTACT

Cell: +1-443-***-****

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