Available to hire
Hi, I’m Van Anh Le, a full stack data scientist with over eight years of experience creating and deploying innovative data solutions across various industries including aviation, consulting, oil and gas, software, and healthcare. I thrive in fast-paced Agile environments and enjoy collaborating with cross-functional teams to deliver impactful AI-driven products and features.
My technical expertise spans multiple programming languages, cloud platforms, and MLOps tools, and I’m passionate about leveraging data to solve complex problems. I look forward to connecting with like-minded professionals and continuing to contribute to the advancement of AI and machine learning technologies.
Language
English
Advanced
Vietnamese
Fluent
Work Experience
Data Scientist at The Boeing Company
July 1, 2022 - PresentDeveloped predictive maintenance models with flight sensor data, achieving an 85% F1-score and reducing unplanned maintenance by 25%. Led MLOps stack development in Databricks for anomaly detection using AutoEncoder. Developed a Catboost model for flight ETA estimation, improving accuracy by 25%. Implemented community-driven federated machine learning with Databricks, improving F1-scores by 20% across fleets, resulting in a global patent application. Built a chatbot for aircraft fault codes with 97% accuracy and fine-tuned LLMs for maintenance records categorization to 95% accuracy, enhancing maintenance efficiency by 20%. Collaborated in Agile teams with airlines and product owners to integrate AI features.
Machine Learning Engineer at Suncor Energy
July 1, 2022 - August 1, 2025Developed an optimization algorithm combining predictive models and Bayesian optimization that increased plant output by 12%. Led MLOps practices with MLflow and Azure Machine Learning and orchestrated workflows with Azure DevOps. Designed Streamlit dashboards on Azure Web Apps for business users and subject matter experts. Built KPI calculation pipelines with Azure Databricks and Azure Data Factory. Created Power BI dashboards for user engagement and KPIs. Reduced pipeline downtime by 50% via proactive EDA and data quality checks. Applied test-driven development with Pytest for ML pipelines.
Data Science Co-op at Suncor Energy
August 31, 2021 - August 1, 2025Developed an optimization algorithm combining predictive models and Bayesian optimization to recommend controller setpoints, improving output by 12%. Led MLOps practices and implemented model lifecycle management with MLflow and Azure Machine Learning. Developed dashboards with Streamlit and Power BI for business and technical users. Implemented data quality checks and data drift monitoring.
Data Science Intern at IBM Canada
May 31, 2020 - August 1, 2025Developed an ensemble stacking model to forecast subscription churn for a music streaming service. Standardized end-to-end data science workflows with Kedro, MLflow, and Airflow. Containerized and deployed the algorithm on Kubernetes clusters on IBM Cloud and Digital Ocean, scheduling daily predictions. Collaborated with software engineers on feature implementation and A/B testing.
Research and Teaching Assistant at University of Calgary
December 31, 2020 - August 1, 2025Developed image-based eczema severity rating pipeline with 96% accuracy and deployed via REST APIs for patient treatment plans. Created a video-based deep learning method to track unmarked mice with a Streamlit web app. Developed a recurrent 3D convolutional network for rodent behavior recognition matching human performance at 76.5% accuracy. Automated rodent sleep assessment using LSTM networks with 95.6% overlap to benchmarks. Developed and managed lab sessions, including evaluating student work.
Lecturer at Electric Power University
March 1, 2016 - August 1, 2025Taught PLC programming, Control Systems, Adaptive Control, and Microcontroller courses. Designed labs and supervised undergraduate projects in PLC programming and microcontroller.
Software Developer at Luvina Software JSC
February 28, 2010 - August 1, 2025Integrated software components and third-party programs. Wrote C/C++ unit and integration tests. Experienced with simulation and optimization software.
Data Scientist at The Boeing Company
July 1, 2022 - PresentDeveloped predictive maintenance models for aircraft components, enhancing airlines’ maintenance strategies with an average F1-score of 85%, resulting in a 25% decrease in unplanned maintenance. Led development and implementation of MLOps stacks in Databricks for anomaly detection with AutoEncoder. Developed ETA prediction models using Catboost deployed as APIs improving MAE by 25%. Created a federated machine learning solution, resulting in a global patent application, and built a maintenance chatbot with 97% accuracy. Fine-tuned LLMs for categorizing maintenance records, improving efficiency by 20%. Collaborated with Airlines, Product Owners, Data Engineers, and developers in Agile settings to integrate AI features.
Machine Learning Engineer at Suncor Energy
July 1, 2022 - August 1, 2025Developed optimization algorithms combining predictive models and Bayesian optimization, increasing plant output by 12%. Led MLOps initiatives with MLflow and Azure ML, orchestrating workflows via Azure DevOps. Designed and deployed dashboards using Streamlit and Power BI for stakeholder interaction and KPI tracking. Implemented EDA and data quality checks, reducing pipeline downtime by 50%. Applied Test Driven Development for machine learning pipelines using Pytest.
Data Science Co-op at Suncor Energy
August 31, 2021 - August 1, 2025Worked on optimization algorithms and MLOps best practices. Built dashboards and pipelines for KPI metrics tracking. Proactively collaborated with subject matter experts performing exploratory data analysis and data quality monitoring to decrease pipeline downtime.
Data Science Intern at IBM Canada
May 31, 2020 - August 1, 2025Developed an ensemble model to forecast subscription churn for a music streaming service. Standardized data science workflows with Kedro, MLflow, and Airflow. Containerized and scaled the algorithm on Kubernetes clusters, scheduled workflows for daily predictions. Collaborated with software engineers on feature implementations and A/B testing.
Research and Teaching Assistant at University of Calgary
December 31, 2020 - August 1, 2025Developed image-based eczema severity rating pipelines with 96% accuracy. Built video-based tracking and behavior recognition methods for rodents using deep learning, achieving performance comparable to human annotators and benchmarks. Automated sleep assessment using LSTM networks on extensive video data. Developed labs, managed sessions, and graded student work.
Lecturer at Electric Power University
March 1, 2016 - August 1, 2025Taught courses including PLC programming, Control Systems, Adaptive Control, and Microcontroller. Designed labs and supervised undergraduate projects.
Software Developer at Luvina Software JSC
February 28, 2010 - August 1, 2025Integrated software components and third-party programs. Developed unit and integration tests in C/C++, worked with simulation and optimization software.
Education
PhD at University of Calgary
September 1, 2016 - January 1, 2023MSc at Southern Taiwan University of Science and Technology
January 1, 2007 - December 31, 2009BSc at Hanoi University of Science and Technology
January 1, 2003 - December 31, 2007PhD at University of Calgary
September 1, 2016 - January 1, 2023MSc at Southern Taiwan University of Science and Technology
January 1, 2007 - December 31, 2009BSc at Hanoi University of Science and Technology
January 1, 2003 - December 31, 2007Qualifications
Industry Experience
Transportation & Logistics, Energy & Utilities, Software & Internet, Healthcare, Professional Services
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