Contact Info

Email: jwmartinez13@gmail.com
Number: (240) 441-8353

Certifications

Certified Entry-Level Python Programmer (PCEP)

Programming Languages

CSS

HTML

Java

Javascript

Python

R

SQL

Unix

Cloud Skills

AWS API Gateway

AWS Comprehend

AWS Lambda

AWS API S3

Git

Tableau

Software Skills

Databricks

Eclipse

SQL

Jupyter Notebook

Microsoft Office

MySQL

OpenRefine

Postman

Qualtrics

R Studio

Visual Studio Code

JOSE
MARTINEZ

DATA ANALYTICS RECENT GRADUATE

About Me

I am a Recent graduate with a bachelor’s degree in Information Sciences. Aspiring to apply strong analytical, research, and technical skills to the Data Analytics field. Seeking to leverage data analytical skills to join a team working on initiatives leveraging data, data science, and other innovative technologies.

Education

B.S., Information Sciences | University of Maryland - College Park

Simulated real world work environment with group-based projects and github collaboration.

Work Experience

Executive Resource Intern | National Nuclear Security Administration
May 2018 - Oct 2018

Assisted in the creation of the Executive Resource webpages;
Maintained various administrative reports and databases;
Prepared spreadsheets and PowerPoint presentations for the Director of the Human Resources;
Provided general administrative support and other-directed tasks to the head of Executive Resources Division;
Assisted in office tasks such as creating/maintaining documents, organization charts, and faxing/scanning documents; and
Ensured benefits and retirement accountability by supporting the Executive Resources Division with the executive and staff benefit plans.

Java Trainee | FDM Group
May 2018 - Oct 2018

Weekly projects and assessments were given to ensure that the material was being comprehended;
Built a Command Line Tool using Unix that allowed for recycling and restoring files/directories;
Using a TDD approach, an employee directory was created in Java that could successfully read and write to a Oracle SQL database by using the Java Persistence API (JPA);

Projects

Sentiment Analysis using Tweets

Conducted Sentiment Analysis of Tweets using serverless AWS services to support the back-end of an HTML site.
- Created sequence diagrams using ZenUML, and a mockup of Website using Moqup as apart of the initial research phase;
- AWS Lambda hosted the Python Script used to connect to AWS Comprehend, AWS API Gateway, AWS S3, and the Twitter API;
- Used Python to connect to the necessary APIs, extract Tweet data using the Tweepy library, format JSON data, and return a response back to an API endpoint;
- The front-end of the website is made using HTML and is comprised of two main components: a form which submits a user search, and a table to display the results;
- Javascript is used to connect the website to the API endpoint, parse the JSON data, and then append the data to the HTML table.
Gentrification & Criminal Activity in DC

Conducted analysis/visualizations using numerous datasets provided by Open Data DC and then analyzed with Python and Tableau.
- Worked with a 4-student team to conduct analysis of datasets provided by opendata.dc.gov
- Used pre-existing datasets that related to Building Permits, Median Income, and Criminal Activity within DC;
- Data cleaning was performed in OpenRefine to both reduce the datasets and to ensure data was useable;
- Utilized Python to read in datasets, create data frames using Pandas library, and create visualization using Matplotlib library;
- To supplement the visualizations used in Matplotlib, Tableau was used to create more meaningful visualizations in a shorter amount of time
- Lastly, created a python notebook using Jupyter Notebook that detailed the steps that were taken throughout the analysis, the results of the analysis, and a discussion of what the results entailed.
Analysis of Tweets

Used the Library Tweepy within Python to connect to the Twitter API. The Pandas & Matplotlib libraries were used to conduct analysis.
- Connected to Twitter’s API by using the Python library, Tweepy;
- Python was used to develop the code, and the code was split up into two classes: one for connecting to the API and retrieving the data in the form of a list, and the second class’ purpose was used for analysis; and
- Pandas were used to create data frames that would allow for us to analyze the data, and the Matplotlib library was used for creating our data visualizations.
Small Retailer Database

Constructed a relational database and ERD using normalization in MySQL filled with hypothetical data.
- Worked with a 3-student team to create a working database and developed nine tables that were linked to one another through primary and foreign keys;
- MySQL Workbench was used to create the database and to populate it with data we used Microsoft Excel. Once the data was completed, the team extracted it in a csv format and uploaded it to MySQL Workbench; and
- Lastly, to test that the database was working, we came up with several SQL queries to ensure that all aspects of the database were working.
Survey for PG County Parks & Rec Department

Created a survey using Qualtrics that aimed to increase participation and promote inclusivity of underrepresented communities in PG county.
- Worked with a 4-student team to create a survey to increase participation and promote inclusivity of underrepresented communities in PG county;
- Was in charge of keeping group on track for completing milestones due to very strict timeline, served as the liaison between the Latino community and the group, and conducting the survey testing;
- Initial research was conducted in an attempt to create a survey that was engaging and information-seeking;
- Two rounds of survey testing were carried out with Latino members of the PG community;
- Lastly, close contact was kept with client to ensure that they involved with the survey design; and
- A set of deliverables were passed on to the client so that it may be administered at sanctioned events and posted to their website.

Courses

Kaggle Data Science Course
June 2020 - Present

Completed the 15 free courses provided by Kaggle which include courses ranging from Natural Language Processing to SQL;
Completing the courses has allowed for a greater understanding of Machine Learning while also at the same time enhancing skills with using Python Libraries;
These libraries include but aren’t limited to Pandas, Matplotlib, Seaborn, GeoPandas, and many more;
Currently applying knowledge from these courses to competitions within Kaggle;
Some of these competitions include: using credit, housing, and payment data to create an algorithm that’ll predict if an applicant can pay off their loan; and
Using Natural Language Processing to build a NLI model that assigns labels to pairs of premises and hypotheses;
Created a map of the U.S. displaying sentiments of tweets using a large dataset provided from one of the courses, cleaned the data using OpenRefine, and manipulated the data using Pandas;
Certifications of completion can be provided upon request.