Shih-Hsiang Lin

480-***-****, adkbv1@r.postjobfree.com, https://www.linkedin.com/in/slin93/

Summary

Actively seeking a full-time position with strong passions and knowledge in mathematical modeling, and use my strengths wisely for the good and give back to the world.

Proficiencies & Skills

Python, SQL, JMP, R, AMPL, Microsoft Suite, Excel, Word, PowerPoint, Power BI, Window Access

Education

Master of Science in Industrial Engineering

Aug. 2018 – May. 2020

Arizona State University, Tempe AZ

Courses: Time series Analysis & Forecasting, Data Science System Decision Analyst, Data mining

Design and Analysis of Experiments, Stochastic & Application Deterministic Operations Research

Bachelor of Engineering in Bioenvironmental Systems Engineering

Sep. 2012 – Jun. 2016

National Taiwan University, Taipei Taiwan

Professional Experience

Data Analyst Intern

Tempe, AZ

Fortech Energy Inc.

Aug. 2020 – Jan. 2021

Working knowledge of current techniques and approaches in machine learning

Assisted to build NLP model in Python to analyze customer survey sentiment and used for future marketing strategy

Visualized positive/negative comment-sentiment relationship with dates to review the performance

Developed SQL queries of high dimensional datasets to generate business insights

Data Analyst Intern

Taipei, Taiwan

Bayer Taiwan Co., Ltd.

Sep. 2017 – May. 2018

Worked with cross-functional departments to keep data initiatives on track, and provided periodic sales performance reporting for the manager to supervise

Processed data including cleaning data, applying statistical analysis in Excel with pivot & vlookup functions

Developed and optimized sales shift scheduling model leading to perfection arrangement and increasing 15% efficient

Built mathematical models to improve distribution time and save up to 10% inventory cost

Identified, analyzed, and executed new or potential products, services, markets, and advertising opportunities

Academic Projects

Time Series Model on Appliances Energy Consumption Dataset

Analyzed time-oriented data, built models in statistical methods and used models for forecasting and prediction

Aimed to forecast energy consumption by analyzing home appliances for energy savings

Successfully selected the best feature within 29 attributes in Python before using time series analysis

Implemented different order Exponential Smoothing, (Seasonal) ARIMA models, Regression models

Achieved the final model after comparing with ACF, PACF, residual plots by visualizing trends and seasonality

Predicted the appliance energy usage for next week, month within a 95% confidence interval

Marketing Strategy in England Area Using Deterministic Operations Research

Translated real-life problems into suitable mathematical models, including production planning, capacity planning,

products scheduling, assignment, transportation, and flow optimization

Selected 25 cities in England and decided the locations of production centers, warehouses

Built mixed-integer model in different approaches to compare with the outcome and used duality properties, sensitivity analysis to improve internal processes

Obtained optimal solutions and carried out analyses from the results in AMPL

Provided sufficient information, detailed viewpoint for the company to make decisions to expand its footprint

Portuguese Bank Telemarketing Analysis

Applied data science and machine learning techniques for the system decision support in Python

Used Python for data cleaning, exploratory analysis, visualization before applying machine learning classification

Built machine learning models in Logistic Regression, KNN, SVM, Decision Tree classifier to train and predict the outcomes

Selected the appropriate model with the lowest error within different classification algorithms

Concluded target customers for bank owner to make better marketing strategies

Analysis of Rainwater Redistribution in South India Using Goal Optimization

Applied urban operations research technique to solve Network flows problem

Selected 14 cities in South India and the goal is to satisfy every local demand of water

Built linear deterministic models in different goal optimization including minimum cost, shortest path, maximum flow

Compared the approach to Traveling Salesman Problem to reshape the process

Obtained optimal solutions and carried out analyses from the results in AMPL

Provided reasonable solutions for the government to maximum benefits within limited resource

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