- Experienced Project Manager and Data Analyst with cross-functional teams.
- Enthusiastic about working with diverse groups of people in a multicultural workplace.
- Passionate about dealing with large and complex data sets to discover valuable insights, solve business problems, and make decisions.
SKILL SET:
• Programming Languages: Python, R
• Database Management: MySQL, PySpark
• Data Visualization: Tableau, MS Excel
• Methodologies: Statistical Modeling, Machine Learning Algorithms
• Project Management: MS Project
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Experience
Lighthouse Digital, LLC (Remote) Austin, TX
Marketing Analyst (Experiential Network Project) Jul. 2019 – Aug. 2019
• Analyzed demographic data with data visualization of 15 cities in North America for the company to expand their business about building tech bootcamps in those cities.
• Analyzed the marketing and positioning of 7 competitors and offered the company helpful insights and recommendations.
AzureWave Technologies, Inc. New Taipei City, Taiwan
Deputy Project Manager Mar. 2012 – Feb. 2015
• Led an R&D team of 4 optical engineers for developing 50+ projects to meet customer’s requirements of new smartphone and laptop product lines.
• Improved supply chain management to reduce 10% of key components’ costs.
• Traveled internationally for overseeing manufacturing to maintain at least 95% of yield rate and customer satisfactions.
Senior Optical Engineer May. 2010 – Mar. 2012
• Engineered 50+ optical systems and lenses for new products to offer more options to current and potential clients.
• Defined appropriate criteria for optical testing to verify a high performance of new products are able to pass 100% of quality control testing.
• Optimized, released, and maintained test flows of production to reduce 60% of costs and increase 30% of efficiency.
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Projects
Big Data Seattle, WA
(PySpark, SQL, Data Visualization) Jan. 2020 – Mar. 2020
• Analyzed a dataset named “US Traffic Accident” (3 million records) from Kaggle.
• Performed a series of data visualization for getting insights and patterns of the dataset.
Data Mining Seattle, WA
(Python, NLP, Logistic Regression, SVM, XGBoost) Oct. 2019 – Dec. 2019
• Analyzed a dataset named “Amazon Alexa Review” from Kaggle by using Scikit-Learn and Keras packages, Bag of Words and Word2Vec methods, and supervised machine learning algorithms in Python.
• Explored Natural Language Processing with text preprocessing and text classification for predicting the coming reviews are positive or negative feedback.
• Evaluated and compared the performance of the classification models by using the Confusion Matrix and identified a best model with 81.6% recall and 0.93 AUC score.
Intermediate Analytics Seattle, WA
(R, Logistic Regression, Random Forest) Apr. 2019 – May. 2019
• Analyzed a dataset from Kaggle named “Human Resources Analytics.”
• Modified the imbalanced dataset with over-sampling and under-sampling techniques.
• Experimented Logistic Regression and Random Forest models on the dataset for predicting the potential employees who are going to leave the organization with an accuracy over 90% .