Data Analysis and Visualization

Results-oriented data analyst with a unique blend of hands-on experience in petroleum engineering and a solid foundation in data analytics.
Graduate of a highly selective Data Engineering program by TEKsystems and Per Scholas with over 450+ hours of instructor led training.
Proven track record of collaborating with cross-functional teams to deliver innovative solutions that meet and exceed business objectives.

Operating Systems: Windows, Linux Ubuntu Distribution

Python: Built-in functions, Writing functions, Jupyter Notebook, Data types, Data classes and methods, XML and JSON manipulations.

Database: MariaDB, HeidiSQL, MySQL, MySQL Workbench, SQL, PostgreSQL, PGAdmin

Data Visualization: Tableau, Matplotlib, Plotly, Seaborn

Data Analysis: Pandas, NumPy, Scikit-learn

Model Evaluation: Linear and MultiLinear Regression, Ridge Regression, Cross Validation

Virtualization: Virtual Machine, OpenVPN

Source Control: GitHub, Git, Git Bash

Script Shells: Bash, Git Bash, PowerShell, SQL Shell

RegEx: String manipulations, find files in Bash Shell

Data Analyst

UMS Global (Barker, TX) - Remote

Utilized SQL to extract and transform data from various sources.
Analyzed large datasets to identify trends, patterns, and anomalies.
Developed Tableau dashboard for a client, resulting in a 10% increase in customer retention and 5% increase in customer satisfaction.
Worked closely with other Data Analysts to understand data requirements and deliver effective solutions within specified time interval.

Research Assistant (Resource Employee)

University of Southern California (Los Angeles, CA)

Assisted in gathering and analyzing data on machine learning applications in oil and gas exploration, thus contributing to timely delivery of the project.

Managed department website, reviewing and publishing articles, and keeping news updated and ensuring the integrity and accuracy of data/information released in reports or studies.

Completions Engineer

BP Azerbaijan (Baku, Azerbaijan)

Analyzed drilling processes, efficiency, and outcomes in offshore oilfields.
Generated daily morning reports using OpenWells and developed an Upper and Lower Completion Equipment Specifications catalog for WellPlan (Suite Well Operations Software). Both software included data heavy operations such as analyzing the data fed into the system by the sensors and the equipment reporting mechanisms.

450+ hours of live Data Engineering training for over 15 weeks.

Worked with Python (Pandas, advanced modules e.g., Matplotlib), MariaDB, Apache Spark (Spark Core, Spark SQL), and Python Visualization and Analytics libraries to manage an ETL process for datasets.
Python and PySpark SQL programs were created to read/extract the data from existing JSON files and load it onto the SQL Database according to the specifications found in the mapping document.
Application Front-End was created which asked for user input based on which data was selected/manipulated.
In addition to querying the database and displaying/updating the data using spark dataframe, this application also visualized the data in the form of plots using Matplotlib.
Sent an HTTP request to an API endpoint, received JSON response and loaded the data to the SQL database.