SU LEI YADANAR

ad3ntv@r.postjobfree.com 857-***-**** linkedin.com/in/suleiyadanar github.com/suleiy suleiyadanar.github.io EDUCATION

Bachelor of Science in Computer Science Expected May 2024 Brandeis University • Waltham, MA • GPA 3.8

Relevant Coursework: Data Structures and Algorithms, Software Engineering, Computer Security, Artificial Intelligence, Natural Language Processing, Software Entrepreneurship, Operating Systems, Human-Computer Interaction SKILLS

Programming Languages: Python, Java, C, JavaScript, Typescript, PHP, SQL Data Technologies: MySQL, PostgreSQL, NoSQL, Apache Cassandra, MongoDB, Spark, Kafka, Airflow, Numpy, Pandas, Matplotlib, Tensorflow, PyTorch, Scikit-learn, RabbitMQ, Databricks, Jupyter Notebook, Excel Cloud Technologies: AWS S3, AWS EC2, AWS DynamoDB, IAM Web Technologies: HTML, CSS, React.js, React Native, Node.js, Vue.js, Vite, Nuxt.js, Django, Flask, CMS, DataDog Development Tools: Git, Docker, CI/CD Tableau, Retool, Jira, Atlassian Confluence, Linux Ubuntu, VMWare, Shell WORK EXPERIENCE

Full Stack Software Engineering Intern • EnergySage • Boston, MA • May 2023 – November 2023

• Modified Bulk Local API data pipeline using NoSQL AWS DynamoDB.

• Wrote jest and python unit tests for Django and Vue.js based e-commerce site.

• Resolved bugs flagged from DataDog and Sentry.

• Contributed Django Python scripts for routing services and A/B testings using VWO.

• Built over 30 Vue.js modules in Nuxt.js apps integrated with JavaScript, Typescript, Vite, Scss and Storyblok Headless CMS during web page redesigns.

• Code reviewed in multiple GitHub repositories for different microservices.

• Collaborated within a team of 8 members and closely communicated with the design, marketing and product teams. Data Engineering Intern • Mass General Brigham & Harvard Medical School • Boston, MA • December 2022 – June 2023

• Built ETL pipeline using RabbitMQ and Spark that increased ingestion speed by over 50% of clinical patient records.

• Modified the automation of weekly data ingestion of new medical records using Airflow.

• Created python scripts utilizing Numpy and Pandas to cast CSV file column data types prior to loading into PostgreSQL database, reducing type casting errors and data processing time by 62%.

• Created JSON schemas utilizing Regex to parse medications from RabbitMQ queues and loading into PostgreSQL.

• Data cleaning, modeling and analysis of electronic health records and patient data using Python.

• Actively participated in discussions with Machine Learning engineers to optimize the data pipeline and ETL process. Data Science Intern • Korn Ferry • Boston, MA • April 2022 – August 2022

• Created data visualizations in Jupyter Notebooks using Matplotlib.

• Collaborated with data scientists to understand the business needs of clients and built dashboards in Tableau.

• Processed raw data from Excel and csv files using Python Pandas and Numpy to prepare data for modeling.

• Used scikit-learn to train data and make predictive models for client’s business needs.

• Built REST APIs to map entities to databases in MySQL using Spring controllers and SQL queries. PROJECT EXPERIENCE [ Portfolio ]

ETL for Small Business (Florist)• Cornelia Gifts • GitHub • December 2023 - January 2024

• Implemented Kafa Stream for real-time order data processing.

• Utilized Spark streaming to transform incoming data in Databricks.

• Stored processed order lists into Apache Cassandra for storage of customer order lists.

• Automated confirmation message delivery to consumers for enhanced customer experience. Active Ingredients in Medications • Personal Project • GitHub • October 2023

• Developed an ETL pipeline on AWS EC2 instance, extracting products data of top 10 active ingredients from FDA API.

• Utilized Python Pandas for data transformation and stored the generated CSV files in AWS S3.

• Orchestrated the ETL process using Airflow.

• Created Tableau dashboard for data visualization with charts for visually compelling representations of the dataset. CoffeeKiosk • Personal Project • GitHub • June 2023 - August 2023

• Brainstormed, designed and managed full-stack MERN web app from start to finish.

• Used React.js for creating reusable UI components (multi-field form elements, pop-up window).

• Developed REST APIs with Node.js and Express.js for CRUD data interactions between frontend and MongoDB.

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