Data Analyst

Dhruv Popat

301-***-**** -- College Park, Maryland -- *****.*****@*******.***.***

LinkedIn:https://www.linkedin.com/in/dhruv-popat-8934b5ba/

Tableau Public : https://public.tableau.com/profile/dhruv.popat#!/

EDUCATION

University of Maryland, Robert H. Smith School of Business

College Park, Maryland, USA

Master of Information Systems

December 2020

Terrapin Scholarship for Academic Excellence (GRE : 325, GPA : 3.7)

Nirma University, Institute of Technology

Ahmedabad, Gujarat, India

Bachelors of Electronic Engineering

May 2019

TECHNICAL SKILLS

Certifications:

-Data Science Python Toolkit (Datacamp)

-Data Analytics Fundamentals (AWS)

-Data Science, Python Data Structures (Coursera)

-Google Analytics / Ads

Languages: R, Python, SQL, C++

Tools: Tableau, Google Ads, MATLAB, Excel, DOMO, PowerBI, Jira, ProjectLibre, ArcGIS

PROFESSIONAL EXPERIENCE

Crest Data Systems, India February 2019 - April 2019 Intern, BI and Tableau Developer

Created interactive Tableau Dashboards by integrating SQL Server data for market research and revenue analysis purposes. Our team furnished these reports to a leading Fortune 500 retail company, automating the process through APIs and Excel Macros, saving at least 10 hours per month.

Queried Walmart Retail Link SQL reports to gather insights into seasonal trends through Machine Learning. Through ARIMA Time Series model, big data patterns through US and Canada could be identified, predicted and forecasted.

Evolutionary Systems, India May 2018 - September 2018 Intern, Data Analytics

Recognized through regression modelling the most significant variables in a government provided dataset on Higher Education in India.

Predicted how the constraints would change in significance through time series models and forecasting.

Visualized the weighted parameters through a blend of Python and Tableau, presenting the draft to the stakeholders. Implementing these changes saw an increase in the number of online users by +20%.

Infosenseglobal Inc, India May 2017 - September 2017 Trainee, Data Visualization and Analytics

Implemented a machine learning algorithm that detected possible anomalies in traffic trends.

Trained the model on past data received through traffic feeds, using the same system that was established by the firm in the United States for the Tri-State region

Visualized hotspots for traffic congestion along the Lat-Longs on the national highway, through ArcGis and Tableau.

PROJECTS

Graduate Data Analytics Challenge: Led a team of 6 and secured the first place both overall and for best visualization. We explored the HealthCare dataset through RStudio to detect the most significant variables amongst 150 constraints for the 2 illnesses. Data wrangling was primarily done on Python and the final Business Intelligence summary was provided through SQL queries on Tableau Web Reports.

Regional Data Challenge 2020: Led a team of 4 graduate students to secure first place in data visualization. We cleaned the data for the first two days and then trained a model through different machine learning methods like Random Forest, XGBoost etc. to best explain trends of pedestrian congestion for campus wide events which drove us to come up with the best solution to reduce the carbon footprint in our campus.

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