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+1(XXX) XXX-XXXX XXXXXX Pittsburgh, PA 15213 minli XXXX@XXXX.XXX
Carnegie Mellon University (CMU), GPA: 3.80/4.33
Master of Information Systems Management
Courses: Web Application Development, Linux & Open Source, NoSQL Database Management, Design Thinking, Agile Method,
Cloud Computing, Coding Boot Camp, Distributed System, Data Structure Application Programmers, Database Management, Java.
Beijing Language and Culture University (BLCU)
Bachelor of Management in Information Management and Information System
University of California, Los Angeles (UCLA), Summer Session
Aug 2016 - Sep 2016
Microsoft SQL Server, MySQL, MongoDB, Neo4j, HBase, Cassandra, Redis, PostgreSQL
Linux, Vue.js, Django, Git, Spark, AWS, GCP, Azure, Hadoop, Docker, Kubernetes, Kafka, Samza, Heroku
Student Software Engineer
Jan 2020 - May 2020
· Applied ETL pipeline on more than 60 billion entries log. Designed data schema and stored the processed data into MySQL on AWS.
· Classified the alarm data as “noise” or not using a pre-trained XGBoost model, which reduced 93% of noise. Analyzed under/over
utilized resources for proper resource allocation using Python, which would bring potentially $1.7 Million yearly gain to Navisite.
Full-stack Engineer Intern
May 2019 - Aug 2019
· Refactored the Game Health & LifeSpan Prediction pages using Vue.js framework.
· Implemented a Spark Job in Scala using RDD, DataFrame, and DataSet APIs to process source purchase files for MySQL database.
· Deployed production code on AWS & GCP using Docker containers, Kubernetes and other cloud resources.
Microsoft Search Technology Center (STC) Asia
Office XXXXXX Intern
Jul 2017 - May 2018
· Extracted the data of products from SQL Server using Kusto; used Power BI to visualize data; saved 10 hours/week by auto updating.
· Diagrammed weekly data reports, analyzed product usage data and offered insights to increase product usage.
Customize Your Coffee Web Application Development, CMU
Feb 2020 - May 2020
· Applied Django MVC framework to a coffee web application development. Incrementally implemented functions including blog post
& comment, payment, product purchase, product recommendation, and user profile using Git version control system.
· Implemented backend functionalities using Python and integrated with Braintree payment API. Deployed the application onto AWS.
NYCabs Application for Fare Prediction, Real-time Driver Matching & Ad Recommendation, CMU
Nov 2019 - Jan 2020
· Utilized feature engineering, XGBoost algorithm, and Google HyperTune to train and improve the Machine Learning (ML) model on
Google AI Platform. Built and deployed a Flask app in python on Google App Engine (GAE) for returning cab fare prediction.
· Processed data streams using Kafka Producer; fed messages to Kafka topics on the remote Amazon EMR Samza cluster.
· Consumed and analyzed streams and static files using Samza. Applied a matching algorithm for client-driver pair and an ad recom-
mendation algorithm for client-yelp NYCStore business pair.
· Developed a node.js application that leverages deck.gl and react-map-gl to visualize driver locations and trips. Deployed a complex
pipeline of ML services on GCP (eg. NLP, Speech to Text, Cloud Vision APIs) to construct an end-to-end solution.
Twitter Analytics Multi-tier Web Service on Cloud (Team Project), CMU
Oct 2019 - Nov 2019
· Developed a multi-tier, high-performance Twitter web service that handles high-load queries using Undertow framework, Terraform,
AWS EC2 and Elastic Load Balancer (ELB) service. Implemented Twitter User Recommendation System with Ranking Algorithms.
· Designed database schema for MySQL and HBase, and performed ETL on 1.2TB data with MapReduce in Java on Azure and AWS.
· Optimized the system performance and scalability for read-heavy queries from 5000 to 13000 RPS by applying database index,
connection pool, data replication and etc.
WeCloud Chat Application, CMU
Sep 2019 - Oct 2019
· Developed, containerized, and deployed three microservices using Java Spring Suite, Docker container and a Kubernetes cluster on
GCP: user profile service, login service, and group chat service using Redis’ PubSub feature, Stomp and WebSockets.
· Applied Helm Charts to migrating data from an embedded database to a remote MySQL database.
· Horizontally scaled application using Horizontal Pod Autoscaler (HPA) based on pod metrics. Achieved fault-tolerance with multiple