Duc (Daniel) Ngo

Resume

Senior Data / Business Intelligence Analyst

Work Experience

Senior Data / Business Intelligence Analyst

TORILAB

Hanoi, Vietnam

March 2025 – Present
  • ·Spearheaded the development of 15+ dynamic Looker dashboards and LookML models on GCP by leveraging complex SQL queries and Python scripts to automate core BI workflows, slashing report preparation time by 80%.
  • ·Orchestrated bi-weekly business reporting, presenting to C-suites and senior stakeholders on marketing performance, revenue impact, and AI market trends, driving a 15% uplift in marketing ROI and 50% increase in DAU.
  • ·Championed end-to-end event tracking for 60+ features by defining key metrics with design, aligning development instrumentation, and validating GCP data into LookML dashboards, boosting feature-adoption visibility by 40%.

Team Leader AI - R&D

VNDIRECT

Hanoi, Vietnam

February 2024 – March 2025
  • ·Led a team of 5 members to tackle pressing issues in AI model development, ensuring timely delivery of high-quality solutions by fostering a collaborative and innovative team environment.
  • ·Achieved a 95% accuracy rate in developing a Word Detection from PDF Model, extracting key information while increasing extraction speed by 90% and reducing error rates by 25% using PaddleOCR and PyMuPDF.
  • ·Developed a stock sentiment model using LLM, attaining 90% accuracy and providing a comprehensive view based on forum user sentiment, offering a broader perspective on the overall market for customers.

Marketing Data Analyst

In4mation Insights

Needham, Massachusetts, USA

July 2022 – November 2023
  • ·Employed predictive transaction data to deliver a comprehensive cost analysis of a new loyalty payment program, facilitating informed decision-making strategy.
  • ·Built an interactive Python script to predict future transactions for 10,000+ stores with 90% accuracy, optimizing machine learning models through extensive EDA using Python and SQL of 1M+ historical transactions from 2020 to 2022.
  • ·Presented actionable data-driven insights to stakeholders during weekly and monthly meetings, offering valuable guidance on dataset selection and playing a key role in driving substantial project improvements.

Projects

Stock Picking with Machine Learning

Team of 3
  • ·Achieved a rate of return of 47.35% in 2021 for the top 20 highest companies, 21% higher than the S&P 500, using Lasso, Random Forest, and Stacking methods.
  • ·Constructed a complete financial dataset for S&P 500 companies from 1999 to 2021 from Yahoo Finance using Selenium, BeautifulSoup, and multiprocessing.

Soccer Spatial Analysis

Team of 3
  • ·Built spatial analysis of passing tendencies using linear mixed-effects and global slopes models for five major European leagues in 2018 using the Wyscout dataset.
  • ·Created 100+ animated graphs displaying passing tendencies, key passes and assists, and position zones for every match using ggsoccer and gganimate.