Data Engineering Intern Resume

SUMMARY:

Experience leveraging Python, Matplotlib, Plotly, Seaborn, Scikitlearn, Tensorflow, Keras, Pytorch, TFLearn to build, visualize and fine tune Confidential models for prediction and classification.
Applied Java to write multiple applications including the backend to a HR management software.
SQL and variants experience with performing data operations for business consumption and Confidential tasks.
Built interactive maps to visualize and storytell with geo tagged data. For example, created a geographical mapping of sentiment extracted from tweets based on keyword of choice.
Used Shell Scripting extensively to build and execute SQL scripts, to manage cloud environments, to setup and maint ain deep learning models on AWS, to manage Hadoop clusters and tasks.
Experience parsing data through APIs, web scraping and online catalogs for training Confidential models.
Cleaned structured and unstructured data, scaled and normalized data using Pandas as well as automated data processing with python.
Implemented software development life cycles and Agile methodologies as part of a team.
Worked in a fast - paced dynamic environment to meet software development deadlines.
Organized and led teams to tackle business challenges, document and present findings to leadership and other stakeholders.

COMPETENCIES:

Java, Python, JavaScript, Hadoop, Hive, Pig, MapReduce, Oracle SQL, MySQL, JDBC, Matplotlib, Pandas, Scikit Learn, Tensorflow, Keras, Pytorch, TFLearn, Deep Learning, Natural Language NLP, Image Recognition, Seaborn, Plotly, GeoPlotlib, Geopandas, Basemap, Oracle DB, JDBC, Excel (ODBC), Excel Pivot Tables, Agile, Scrum, SDLC, GeoPandas, Basemap

EXPERIENCE:

Data Engineering Intern

Confidential

Responsibilities:

Learned and a pplied Big Data and Hadoop technologies through hands-on classroom activities and case studies
Prepared large sets of data for further processing using the following technologies: Java, Oracle DB, JDBC, Excel (ODBC), Hadoop, MapReduce, Data Transfer (Sqoop), Pig and Hive
Gained experience on how to extract, scrub and manipulate real-time and warehouse data using SQL & Java
Put new knowledge to properly define business problems and design tests that yield valid solutions
Acquired experience with Project Management (Agile, Scrum) and Software Development Life Cycle (SDLC)

Confidential

Researcher

Responsibilities:

Cleaned unstructured data for data analysis and Confidential tasks and pipelines
Demonstrated data storytelling through extraction and visualization of data insights from different databases
Managed online teams to collaborate and complete data science projects on schedule
Utilized different visualization programming libraries to tell an immersive data story of murder rates in the Confidential from 2001 to 2018
Used Python and the Twitter API to get raw data and preprocesse d it for a data science task
Used Natural Language Processing ML libraries to train a Bayesian model for sentiment analysis with an accuracy of 7 6 % which is better than human performance
Packaged the above model into a web app using Flask, Docker, VM, MySQL and JavaScript

Confidential

Student

Responsibilities:

Cleaned data from various sources for further data analysis
Arranged and participated in group coding activities to facilitate learning and satisfactory project completion
Used a Deep Neural Network to build an image classification Confidential model from the ground up for my capstone project and achieved a 97.89% accuracy at recognizing traffic signs.
Applied Reinforcement Learning to train a smart vehicle to navigate a simulated environment in the shortest amount of time whilst observing all traffic laws and not causing any accidents
Used Decision Trees algorithms to correctly predict the price of houses for a neighborhood in Boston
Used transferred learning to classify images of dogs and correctly identify the dog breed in the test images

Confidential

Campus Associate

Responsibilities:

Logged shipments and package data as well as participated in daily loss prevention data logs
Delivered customer satisfaction and problem-solved scenarios such as missing or damaged packages by accessing proprietary company databases with sensitive customer information
Opened and closed the physical store and covered leadership responsibilities

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