About me
Hello! My name is Steven Dominic Sahar and I am currently a Data Science senior at UC San Diego.
I am a highly motivated individual and have expertise in data science and software engineering. My skills encompass a wide range of technologies, including Python, C++, JavaScript, and the MERN (MongoDB, Express.js, React, Node.js) stack. My passion for leveraging data-driven insights and creating innovative software solutions drives my commitment to excellence in every project I undertake. I am constantly seeking new challenges and opportunities to contribute to the field, and I thrive in dynamic, collaborative environments.
Work Experience
Lids
Information Technology Intern
- Wrote SQL scripts and VBA to automate database queries population into Excel for uploading product data into D365, eliminating manual copy pasting of data, streamlining the process by 55%.
- Wrote a Python script to create sports card combinations, increasing the unique value count by 1200%.
- Created a store classification tool using SQL and VBA for the merchandising team which helps in creating product assortments for 1200 Lids store nationwide. Tool includes sales metrics such as UPT & DPT, averaged over 3 years.
- Developed new components and refactored existing code for the D365 Remediation Portal using Razor.
- Generated over 2000+ test cases, conditions and data for the new Power App based on the design document.
- Wrote SQL queries to forecast product assortments of newly opened stores based on existing sister stores.
Ascend Inc
Data Management Intern
- Developed a Python script to automate EEO-1 data organization into Google spreadsheets, enhancing process efficiency by 60% through elimination of manual inputs.
- Researched the US Census data to uncover the number of immigrants and their contributions to the economy, and visualizing the data using Tableau dashboards and stories.
- Created a Python script to extract data from 1800 Excel files, organizing the data into tables for Tableau.
San Diego Supercomputer Center
Software Engineer Intern
- Created new pages, user features, and optimized existing code for the CAPCHD project with ReactJS.
- Established connections to REST API, enabling the display of database information on the frontend.
- Conducted automated frontend end-to-end testing to ensure data integrity using Jest-Puppeteer, integrated testing with Gitlab CI/CD pipeline, optimizing frontend testing speed and accuracy by 45%.
- Developed Python backend components, facilitating frontend interaction with S3 Bucket and DynamoDB.
- Performed in-depth manual testing on newly implemented features, achieving a 90% reduction in bug reports.
- Fix any bugs present in our deployment environment, utilizing AWS Cloudwatch to help with diagnosis.
San Diego Supercomputer Center
Full-Stack Developer Intern
- Developed a mobile application using MongoDB, ExpressJS, React Native, and NodeJS (MERN) with a team of 7.
- Engineered the full-stack functionality for the Login & Registration System, Review Popup Modal, New Review Submission, Images, Dark & Light Mode, Map Pin Clustering, and Search Bar, improving UX by 20%.
- Worked under the Agile methodologies through daily scrum meetings and bi-weekly sprint reviews.
Project Portofolio
Modelling Salaries on Programming Languages
This is a Python-based project which analyzes the correlation between the number of programming languages an individual possesses and the median salary of software engineers in the United States.
Skills:
EDA · Data Visualization · Correlation · RegressionPower Outage Impact Analysis
This is a Python-based project which analyzes how cause category associate with outage duration, numbers of customers affected, and total price of electricity.
Skills:
EDA · Data Visualization · Hypothesis Testing · ClassificationTWICE Line Distribution
A Python based project which analyzes the line distribution among TWICE members, utilizing web scraping techniques and hypothesis testing methodologies.
Skills:
Web Scraping · Hypothesis TestingUser Car Price Prediction
This is a Python-based regression project which predicts the price of used cars based on the year purchased, mileage, city the car was sold, state the car was sold, VIN, manufacturer and model of the car.
Skills:
EDA · Data Visualization · Regression