ADESH MAHENDRA GADGE

315-***-**** adkrfh@r.postjobfree.com https://www.linkedin.com/in/adesh-gadge https://github.com/adesh-gadge/Data-Science-Portfolio Blog EDUCATION

Syracuse University School of Information Studies, New York May 2020 Master of Science in Applied Data Science, 3.9

Coursework: Analytical Data Mining, Business Analytics, Data Visualization, Big Data Analytics, NLP, Financial Analytics Veermata Jijabai Technological Institute, University of Mumbai, India May 2018 Bachelor of Technology in Electronics Engineering, 3.5 Coursework: Statistics, Data Structure, Neural Networks, Signal Processing, Numerical Techniques TECHNICAL SKILLS

Programming Languages Python, R, SQL, PySpark, PyTorch, C++, Node.js Database Technologies BigQuery, MySQL, Microsoft SQL Server, Hive, MongoDB (NoSQL), SSIS Analytical Tools MS Power BI, Tableau, Excel, R Shiny, Google Data Studio, Dash AWS technologies Redshift, S3, Sagemaker, Lambda

Other Tools MS Office Suite (Outlook, Word, Excel, PowerPoint), Git, Jira WORK EXPERIENCE

Seedstages, Claremont, CA October 2020 – Present

Data Science Intern

• Collecting, labelling and cleaning data with SQL and Python for HR, application usage and analyzing user behavior data

• Defining KPIs, building dashboards with Python & Tableau to help product team make faster, better decisions

• Strategizing ways with the team to collect new data sources and building models to eliminate bias in hiring process

• Analyzing the effect of campaigns, android/iOS app updates effects on user interactions Syracuse University Enrollments Office, Syracuse, NY May 2019 – May 2020 Data Analyst Research Assistant

• Investigated and conducted forecasts on student admission stages for Syracuse University in Python

• Scraped web, cleaned, transformed data with SQL to design live interactive dashboards using Tableau, R Shiny hosted on AWS, to facilitate real-time decision making with KPIs reducing data reporting time by 35%

• Generated reports to present insights and conclusions to team in order to refine strategies and operations Syracuse University, NY August 2019 – December 2019 Graduate Teaching Assistant for IST 718 - Big Data Analytics

• Collaborated with Professor in content design, instructed and mentored students for weekly assignments and final projects Our Ability, Albany, NY April 2019 – August 2019

AI Engineer Intern

• Developed single handedly a chatbot for the job portal to build easier interaction for differently abled people

• Created data pipelines to extract, validate, clean and aggregate recruitment data to Azure SQL Databases

• Utilized Microsoft Azure Bot Framework in Node.js to produce chatbot leveraging Azure Cloud Services

• Collaborated with Microsoft for development, showed an increase in interactions by 40% ACADEMIC PROJECTS

Data Warehousing using dimensional modeling from OLTP Data marts (SQL, Power BI, SSIS, SSAS, SSRS) January 2020 – April 2020

• Designed a data warehouse after a merger between two companies and analyze customer segmentation and satisfaction

• Performed data profiling, data staging, construction of SSIS packages for ETL resulting in customer-product reports with SSRS, SSIS, SSAS and visualizations using Power BI to derive actionable insights from KPIs

• Formulated facts and dimensions from Relational database using Star schemas through data transformation

• Deployed Multidimensional OLAP in system resulted in an increase of querying efficiency by 50% than OLTP Hit-Or-Miss, Song Popularity Prediction (Python, API, Logistic Regression, Random Forest) October 2019 – December 2019

• Devised a method to predict if new upcoming song would be a hit or miss, based on audio features

• Constructed data sets with audio features of hundreds of songs, employing Spotify API and accomplished data preprocessing on it such as, One-Hot-Encoding, Standardization, SMOTE algorithm for up-sampling

• Built Logistic Regression as a base model with AUC=0.63 on unseen data and then trained a tuned Random Forest Model with a 5-fold cross validation with enhanced performance of AUC=0.77 on unseen data Beijing Housing Price Analysis (MS Excel, Regression, Hypothesis Testing, Time Series Analysis) October 2018 – December 2018

• Collaborated with a team of four to analyze factors affecting price of residential units in the Beijing Area

• Executed descriptive statistical analysis on factors, time-series analysis, hypothesis testing, confidence interval, forecasting analysis on housing data with Advanced Microsoft Excel

• Delivered a presentation of project insights to 150+ students and defended a Q&A session

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