WORK EXPERIENCE

OpenNet., Data Analyst, Aug 2024 ~ Now

As a Data Analyst within the Business Intelligence division of OpenNet's Trading Team, I am responsible for supporting betting behavior risk control, ensuring the integrity of market flow's impact on odds estimation, and detecting fraudulent activities among individual users. My role requires proficiency in data engineering, predictive analysis, and risk mitigation to enhance the team's operational efficiency.

Trading Team

• Reduced Peak-Time Data Delay.
  • Spearheaded enhancements to the order statistics analysis system, resulting in a reduction of peak-time data processing delays by 2 hours, improving system responsiveness and data availability.
• Optimized User Intervention Timing.
  • Leveraged behavioral analytics to identify optimal intervention points, leading to a significant reduction in Type 1 and Type 2 errors, enhancing the accuracy and efficiency of fraud detection protocols (Increasing the accuracy rate ~4%).

Alfred Labs., Data Science, Jul 2017 ~ Mar 2024

As an early employee of the company, I played a pivotal role in the development of our data infrastructure. This included the creation of robust ETL pipelines and automated dashboards, key advancements that enabled the entire organization to make data-driven decisions. My expertise in designing experiments, streamlining business metrics, and conducting causal inference analyses, significantly streamlined our decision-making process.
Experience leading a Data Team with three members.

Product and Marketing

• Design the experiments and key metrics for hypothesis verification.
  • Developed an automated A/B testing reporting system that iterates with the latest data, reducing manual effort for Data Analysts (amount half man-day for each project).
  • Unconventional experimental analysis (such as natural experiments, fuzzy RDD, etc.).
  • Optimize the effect of ads and payment pages from 0.8% to 3%.
• Designed and implemented business metrics.
  • Build revenue modules, such as LTV, Subscribe Retention, Conversion Funnel, etc.
  • Auto-sequence system of ads waterfall.
  • Discussions to define North Star metrics, corresponding OKRs, and associated guardrail metrics.
• Categorized different user scenarios based on usage time and various custom labels.
  • The findings of this study were one of the main reasons for launching a major project the following year.
• Quantifying and tracking the user experience.
  • Discovered that what was previously considered a positive indicator actually contradicts the business objectives.
  • Established accurate product quality metrics.
• Analysis of Ratings and Reviews Using Crawlers and LLM.
  • Identify similarities and differences between our products and those of competitors.

Tech Team

• Estimate the order of magnitude of users (for capacity planning).
  • Successfully identified the optimal data center location, minimizing costs while maximizing network performance.
• Clustering the performance of the different computer-vision algorithms.
  • Using NLP as a solution for fixing ANR (Application Not Responding).
• ETL System.
• Internal auto-alarm system.

EDUCATION

University of Taipei, BS, Computer Science, 2012 ~ 2017

Transferred from the Mathematics department to the Computer Science department.

The graduation thesis focused on analyzing user preference for phrases on the message board PTT.

Mathematics

Number theory, Calculus, Linear algebra, Abstract algebra, Probability theory, and Statistics.

Computer Science

Database Systems, Introduction to Machine Learning, Introduction to Image Processing, Introduction to Data Mining, Discrete Mathematics, Java, Data Structures, Digital System Design, Operating Systems, Algorithms, Digital Circuit Laboratory, Computer Network, System Programming, Assembly Language, Computer Architecture, Formal Languages and Automata Theory, Engineering Mathematics, Dynamic Webpage Design, Programming for Mobile Phone, Introduction to Cryptography.

SKILLS

• Python, R, Java, C, Assembly, JavaScript, ReactJS.
• SQL, MongoDB.
• Processing data with Interpretable Machine Learning Model (SVM, Random forest, logistic regression, linear regression, etc.) .
• Experienced in using GCP and AWS
  • BigQuery, GCS, and Data Studio
  • RDS, Redshift, Kafka, FSX, EC2, and S3
  • K8S and Docker
• Visualization tools, such as Plotly and matplotlib.
• ETL pipeline and related tools, such as Airflow.