Nhi Nguyen | Contributor | Calculator Kilo
Nhi Nguyen
Data Scientist | Machine Learning Engineer | PhD in Machine Learning
This data scientist and machine‑learning engineer brings a rare blend of academic rigor and industry experience. After earning a Ph.D. in Electrical Engineering from the University of Illinois Chicago in 2010—where her dissertation explored geometric, kernel‑based and symbolic‑sequence approaches to signal‑processing problems—and a Bachelor’s degree in Electronic Engineering and Information Science from the University of Science and Technology of China, she embarked on a career that spans research labs, energy companies, e‑commerce platforms and tech giants.
Professional background and credentials
She began as a research intern at eBay (2008–2009), developing machine‑learning models for product classification and buyer fraud detection, then served as a Research Fellow in Data Mining at the University of Michigan (2010–2011), focusing on social‑network analysis and natural‑language processing. In industry, she spent six years at CGG (2011–2017) leading geo‑data processing teams and projects, followed by roles as a Staff Data Scientist at GE Oil & Gas (2017–2018), where she built predictive‑maintenance and optimization systems, and Principal Data Scientist at Equinor (2018–2021), tackling forecasting and anomaly‑detection challenges in commodity trading.
In late 2021 she joined Shopify as a Senior Data Scientist, leading initiatives in logistics forecasting, ads growth and A/B testing; her work there improved planning accuracy and accelerated experimentation. Since May 2024, she has been a Senior Data Scientist at Microsoft, working remotely from Houston on advanced machine‑learning projects that support strategic decision‑making.
Across these roles, she has developed expertise in predictive modelling, signal processing, anomaly detection, logistics forecasting and digital advertising analytics. Her technical toolkit includes cloud platforms (Microsoft Azure, Google Cloud), distributed‑data technologies (Apache Spark, Apache Spark Streaming), deep‑learning frameworks (PyTorch, Keras, TensorFlow), and programming languages such as Python, SQL, C++ and Perl. She is skilled in data mining, statistical modelling, numerical analysis, data visualization and pattern recognition, and has experience with DevOps and MLOps workflows (Azure DevOps, cloud computing). Colleagues endorse her for her strong analytic capabilities, programming acumen and ability to translate machine‑learning research into high‑impact industrial solutions.