Data Engineer

Location:

Fremont, CA

Posted:

November 02, 2020

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Resume:

PH.D. HUILIN CHANG

USA 213-***-**** *******.*****@*****.***

Professional Summary

• Real world experiences R/R shiny server to populate automatic data pine lines and dashboard reporting systems

• Experienced Scrum & Agile software Engineering & CD/CI pipeline

• Project management experiences – PM in TSMC/Samsung

• Currently joining University of Virginia online MS in Data Science (expected Dec. 2020)

• Hold PHD in Engineering and Master in Master of Business Administration

• Programming and scripting languages: Python, PyTorch, Tensor flow, SQL, Dynamic SQL, BigQuery, C++, Java, JavaScript, PHP, HTML, R programming, Ruby on Rails, Web scraping and Beautiful Soup, Kali Linux.

• Critical thinking in Data Science and Statistical analysis in Big data Hadoop (Pig, Hive, Map Reduce). Engaging Agile daily stand-up project for teamwork delivery.

• Well-published, with several science journal papers in the fields of mechanical properties, material characterization, reliability, nanotechnology, and mathematics of electrical fields.

• Github: https://github.com/gladieschanggoodluck

Projects

• FIFA project – used python to build up app and interactive plots : https://www.hemanshakeri.com/posts/2019/12/fifaapp/

• NLP project using tensor flow, Pytorch built training models from text collection, actionable insights and visualization.

o AMAZON Review sentimental analysis: https://github.com/gladieschanggoodluck/NLP-Amazon o NLP auto-complete, machine translation, topic modeling https://github.com/gladieschanggoodluck/NLP-AutoComplte-

Preprocessing and feature engineering

Supervised learning/unsupervised learning

Language model

Evaluation & deployment

o NLP Deep Learning (Stanford project) https://github.com/gladieschanggoodluck/NLP- DeepLearning-

• Tableau and Python project – FIFA :

https://github.com/gladieschanggoodluck/UVA_2019_SemesterProject_Learning/blob/master/README.m d

• Web developer projects:

o To Do List: https://todoster-gladies-chang.herokuapp.com/ o Quote everyday: https://splurty-gladies-chang.herokuapp.com/ o Nomster: https://nomster-gladies-chang.herokuapp.com/ o Grammable : https://grammable-gladies-chang.herokuapp.com/

• R projects:

o Using R to construct Machine learning in Haiti project/Adult project successfully received acceptable model accuracy and selections

https://github.com/gladieschanggoodluck/Haiti-Project

https://github.com/gladieschanggoodluck/Stat6021 Skills

• Mechanical engineering

• Machine Learning (Python, R)

• Electrical engineering

• Mathematics expertise

• Modeling: Simple Liner regression (SLR)/Muli-

linear regression (MLR)/TCAD

• Web app: Ruby on Rails, Java Script

• LabVIEW, EXCEL, VBA, SPSS

• SQL/NoSQL, airflow on Kubernetes

• Database management(Polyglot)

• Scrips: shell coding, polyglot

• Cloud service: AWS(S3, Glue, Lambda, Athena),

GCP, Rivana

• Data science/Data Wrangling: Programming &

Software testing and Debugging, SAS, R, Java,

Python, Keras, NLP, C++, SQL, Dynamic SQL

• Project management- Scrum/Agile process

• Software, web application, software testing (TDD, Unit Testing) and debugging

• Big data- Hadoop, PySpark

• Data preprocessing/Mining-

Informatica/talend/pentaho ETL,

Kafka/zoomkeeper data streaming

• Data Visualization: Tableau, R, Python

• ML libraries/algorithms: scikit-learn, XGBoost,

MXNet, Tensorflow, Pytorch, NLTK

• Trilingual speaker (Mandarin, Korean, English)

Work History

Senior Technologist 02/2019-09/2019

Western Digital – Milpitas, CA

• Used ETL processes to wrangle data and improve efficiency, performing data migration for big data

• Used Bayesian Model Averaging Regression for predictive analysis, data mining 3

• Used Machine Learning/Tensor flow for 3D NAND project to predict WLs dependency on Memory failure rates from model selections to best model recommendation

• Memory lookup algorithms/data management including Informatica/talend ETL pipeline, complex SQL scripts& Java to predict reliability, read, write performance, data presentation with Looker

• Assisted Engineers for WAT test reporting using Excel VBA: auto-gen reporting/In-line parametric monitoring timely update

• 3D Memory reliability test algorithm in C++/Python for performance classification

• Used Machine Learning/Tensor flow for 3D NAND project to predict WLs dependency on Memory failure rates in SAS Hadoop JVM ecosystem

• Cansandra/NoSQL database – big data execution served for streaming data and database scaled up.

• Worked on Big Data Integration &Analytics based on Spark, Kafka, Zookeeper and web Methods. Senior Engineer 02/2018 to 01/2019

Micron Technology – Manassas, VA

• Applied machine learning for sensors’ data from critical equipment for predictive maintenance to forecast the failure rates and suggested preventive maintenance based on the model.

• Inline parametric chart establishment & synced tool status project: Informatica/talend, used SQL data query & VBA for auto-gen synced with scheduling time setup

• Prob/Yield data management & trend chart: used Tableau for data visualization & table management synced to database and provided updates on a timely basis and highlighted flagged parameters from prob/Yield tests

• Experienced Microsoft SQL server, ETL/BI solutions for Big data ecosystem establishment

• Spark project: streaming data producer/consumer from API and execute data wrangling and link to SQL to data warehouse followed by data analysis and dashboard establishment

• Dedicated to memory periphery performance linked to CPU performance monitoring

• Automated ETL processes to wrangle data, resource application and failure flagging Senior Member Of Technical Staff /Automation & infrastructure team 10/2016 to 01/2018 Globalfoundries – Malta, NY

• CPU/GPU device report data extraction & auto-gen project: Informatica/talend, auto-gen reporting at Shiny R server using SQL query & JMP to get auto reporting/plotting

• Product status synced to online reporting project: linked to data base server with SQL query for auto plotting using Python for post data processing

• Collaborated with internal stakeholders, identifying and gathering analytical requirements for customer, product and projects needs

• Big data/cloud-based project: airflow on Kubernetes to schedule task/data warehouse and SQL execution Principal Engineer 10/2009 to 03/2016

Samsung Electronics – Seoul, South Korea

• WAT/Yield auto-gen project: VBA tool for WAT/Yield auto-gen reporting and parametric monitoring with excel for plotting and Anova analysis

• Dedicated CPU processor design/debugging/performance testing

• Worked with internal marketing as well as business units to shape future core development

• Managed a planning team to drive technology road map and process flow and product delivery. Technical Manager 08/2002 to 08/2009

Taiwan Semiconductor Manufacturing Company – HsinChu, Taiwan

• Demonstrated customer-oriented project leadership in highly competitive environments, with a record of customer satisfaction.

• Using statistical analysis, such as Octave, Matlab, and C ++ programming to facilitate systematic FA data analysis.

• Dedicated image senor/GPU mass production, performance testing and product delivery Education

Ph.D.: Material Science and Engineering

National Chiao Tung University - Taiwan

• Majored in Nano Technology, Electrical device characterization

• 1999-2002

MBA: EMBA Specific

National Chiao Tung University - Taiwan

2008-2010

Master of Science: Data Science

University of Virginia (MS-Data Science) - Charlottesville, VA 2019-2021

Machine learning & Deep learning, Algorithms, Dynamic SQL CNN & RNN application for blue-tarp project for image processing Big data streaming: implementing Kafka producer and consumer on Kafka cluster setup with help of zookeeper Certifications

• Stanford University – Natural Language Processing and Deep Learning (X5059A9)

• Stanford University - Project Management (X363147)

• Technical Support Fundamentals (Coursera)

• Deep learning- Improving Deep Neural Networks Hyperparameter tuning. Regularization and Optimization (Coursera)

• Deep learning-Structuring Machine Learning Projects (Coursera)

• Deep learning-Neural Networks and Deep Learning (Coursera)

• Python Data Structures (Coursera)

• Programming for Everybody - Getting Started with Python (Coursera)

• Digital Strategies Business Leading the Next-Generation Enterprise (Emeritus)

• Applied Data Science (Emeritus)

• Berkeley Boot Camp : 3 Ruby projects and 3 CRUD app using Node.js/MongoDB

• Getting Started with SAS Programming(Coursea)

• Doing More with SAS Programming(Coursea)

Yours sincerely, Huilin(Gladies) Chang

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