Computer Science Machine Learning

LEYKI REYNOSO JR

517-***-**** **************@*****.*** www.linkedin.com/in/leyki-reynoso-jr-b0b9a5141

github.com/Leyki-Reynoso

EDUCATION

NEW JERSEY INSTITUTE OF

TECHNOLOGY

Bachelor of Science, Computer Science

BERGEN COMMUNITY COLLEGE

Associate of Science, Computer Science

Graduacion: May 2023

Graduacion: June 2020

SKILLS

Programming: z/OS, USS, Rexx, COBOL, IMS, TSO/ISPF, SDSF, JCL, SMPE, CICS, Python, SQL, HTML, CSS, JavaScript, React Native, Django, C, Bash, MATLAB, PHP, Git, Java.

Relevant courses: IBM Z Xplorer, Master the Mainframe 2018, Data Science, Calculus III, Linear Algebra, Data Structures and Algorithms, Web Development. EXPERIENCE

Technology Analyst – August 2023 - June 2024

Fiserv, Berkeley Heights, NJ

● Implemented Cucumber and JUnit on Java for automated testing.

● Automated the testing process in the company's pipeline using java.

● Used Java and Spark to efficiently create synthetic data, improving testing effectiveness. Software Developer – September 2022 – July 2023

ScanAvert, UrRecalls solution/project work, Newark, NJ

● Managed backend infrastructure with WinSCP on AWS.

● Handled database management using Django in Python.

● Upgraded react-navigation dependencies and updated JavaScript, HTML, and CSS files.

● Integrated the Sifter API to provide accurate food product information. Laboratory Technician – March 2022 – March 2023

New Jersey Institute of Technology, Newark, NJ

● Provided technical support for professors, students, and classroom equipment.

● Conducted routine maintenance checks to ensure functionality of classroom technology.

● Assisted with departmental tasks to support smooth operations. CERTIFICATES

Google Data Analytics - Coursera[link]

● Developed key analytical skills in data cleaning, analysis, and visualization using tools such as spreadsheets, SQL, R programming, and Tableau.

● Cleaned, organized, and analyzed data for calculations and insights using spreadsheets, SQL, and R. Data Scientist: Machine Learning - codecademy[link]

● Mastered data analysis techniques including data cleaning, exploration, and feature engineering to prepare datasets for machine learning models.

● Developed skills in Python, SQL, and machine learning libraries to efficiently manipulate and analyze datasets.

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