Available to hire
I’m a data scientist with a robust background in AI, machine learning, and data science, currently leading the development of AI-driven products at Laerdal Medical. I design and deploy scalable AI solutions that solve real-world problems and deliver tangible impact across product, UX, data, and operations teams.
I designed a dynamic and efficient RAG pipeline and a modular evaluation framework that enables rapid public demo stages and high user engagement. I’m excited to leverage my experience with scalable deployment, AI technologies, and predictive analytics to drive innovation and business growth.
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Language
English
Fluent
Vietnamese
Advanced
Finnish
Advanced
Work Experience
Data Scientist at Laerdal Medical
January 1, 2024 - PresentLed the end-to-end delivery of the company’s first AI-driven product, collaborating with Product, UX, Data, and SRE teams to progress from concept to public demo within three months. Developed a modular evaluation framework benchmarking each layer of the RAG stack to identify optimal performing combinations. Evolved prototype into an agentic RAG pipeline featuring dynamic tool selection, self-reflection, and adaptive reasoning modules with automatic chaining, critique, and retry capabilities. Deployed and scaled the service for over 5000 concurrent users using Docker containers hosted on Azure App Service, automated CI/CD with GitHub Actions, and implemented async I/O validated through Locust. Maintained and enhanced an internal employee chatbot handling 500+ daily sessions by shipping new features, eliminating defects, and sustaining 99% uptime, while integrating agent-based planning, self-evaluation, and memory-augmented context. Fine-tuned the chatbot’s Llama-38B model using LoR
Data Scientist at Kongsberg Maritime
January 1, 2024 - August 10, 2025Utilized Databricks to process and analyze large-scale datasets, developing, testing, and orchestrating over 30 automated daily data workflows to boost operational efficiency. Engineered predictive maintenance models to forecast equipment failures and assess associated costs. Conducted comparative fuel consumption analyses to highlight engine performance improvements. Designed and implemented a time-series anomaly detection system for vessel equipment utilizing MLflow for automated model retraining, leading to significant client cost savings and securing additional contracts. Applied large language models to classify service reports, detect safety issues and non-conformities, and developed a RAG component to improve information extraction and report usability. Created a hybrid multi-class classification algorithm integrating expert-defined rules with alarm signal data, combining time-series analytics and NLP to increase accuracy and speed of alarm identification. Collaborated with the
Digital Graduate at Kongsberg Maritime
January 1, 2019 - August 10, 2025Developed a deep learning-based anomaly detector to identify issues with diesel engines, contributing to operational reliability and maintenance prediction.
Digital Graduate at Rolls-Royce Commercial Marine
January 1, 2019 - August 10, 2025Visualized ship trajectory predictions using AIS and INS data leveraging tools like OpenCV, smopy, and folium. Predicted stationary vessels' relative headings using image data to comply with COLREG. Projected vessel trajectories based on AIS data employing LSTM models.
Giant Leap Intern in AI at Vaisala
January 1, 2018 - August 10, 2025Created a contract classifying program for locating legal documents within the company network working with both English and Finnish languages, utilizing NLP with OCR.
Data Scientist at Laerdal Medical
November 1, 2024 - PresentLead the end-to-end delivery of the company's first AI-driven product by collaborating with Product, UX, Data, and SRE teams to translate unstructured business challenges into a well-defined AI engineering project, achieving a public demo within 3 months. Developed a modular evaluation framework that benchmarks every layer of the RAG stack (LLM, embeddings, vector index, prompt template, retrieval strategy) to surface the best-performing combinations and inform component selection. Transformed a naïve RAG into an agentic RAG pipeline with evaluation-first multi-retrieval and self-reflection steps, emphasizing continuous improvement and practical deployment of the workflow. Deployed and scaled the service by containerizing with Docker, hosting on Azure App Service, automating CI/CD via GitHub Actions, and optimizing async I/O and memory management. Maintained an internal employee chatbot with 500+ daily sessions, integrating agent-based planning and self-evaluation while sustaining 99%
Data Scientist at Kongsberg Maritime
November 1, 2024 - September 7, 2025Designed and implemented a time-series anomaly detection system for vessel equipment using MLflow for automated model retraining; leveraged Databricks to process and analyze large-scale datasets and orchestrate over 30 automated daily data workflows to improve operational efficiency. Developed predictive maintenance models to forecast equipment failures and assess associated cost impacts; conducted comparative fuel consumption analyses to highlight engine performance improvements. Created a hybrid multiclass classification algorithm by integrating expert-defined rules with alarm signal data, combining time-series analytics and NLP to increase the accuracy and speed of alarm identification. Applied large language models to classify service reports, detect safety issues and non-conformities, and developed an RAG component to improve information extraction and report usability. Collaborated with the Propulsion Digital Twin team to design and deliver customer-facing dashboards, directly co
Digital Graduate at Kongsberg Maritime
November 1, 2019 - September 7, 2025Digital Graduate program participant focusing on engine analytics and anomaly detection. Detected issues with engines using a Deep Learning-based anomaly detector.
Digital Graduate at Rolls-Royce Commercial Marine
May 1, 2019 - September 7, 2025Visualized ship trajectory predictions using AIS and INS data with OpenCV, smopy, and folium. Predicted stationary vessels' relative headings using image data to comply with COLREG, improving maritime safety and navigation accuracy. Projected vessel trajectories based on AIS data using an LSTM, enhancing predictive accuracy and aiding in collision avoidance.
Giant Leap Intern in AI at Vaisala
August 1, 2018 - September 7, 2025Created a contract classifying program for locating legal documents in the company network, working with both English and Finnish, utilizing NLP with OCR.
Data Scientist at Laerdal Medical
November 1, 2024 - PresentLead the end-to-end delivery of the company’s first AI-driven product, collaborating with Product, UX, Data, and SRE teams to translate unstructured business challenges into a defined AI engineering project, achieving a public demo within 3 months. Developed a modular evaluation framework to benchmark every layer of the RAG stack (LLM, embeddings, vector index, prompt templates, retrieval strategy) and inform component selection. Evolved a naïve RAG into an agentic RAG pipeline with evaluation-first multi-retrieval and self-reflection steps. Containerized services with Docker, hosted on Azure App Service, and automated CI/CD via GitHub Actions. Maintained an internal chatbot with 500+ daily sessions and 99% uptime; fine-tuned Llama-3 8B with LoRA adapters to reduce memory and training time.
Data Scientist at Kongsberg Maritime
November 1, 2024 - September 7, 2025Designed and implemented a time-series anomaly detection system for vessel equipment, using MLflow for automated model retraining. Processed large-scale datasets with Databricks, orchestrating over 30 automated daily data workflows. Built predictive maintenance models and conducted cost analyses to highlight improvements. Implemented a hybrid multiclass classification combining expert rules with alarm signals, and applied large language models to classify service reports, detect safety issues, and enhance information extraction with a RAG component. Collaborated with the Propulsion Digital Twin team to deliver customer dashboards and built real-time Grafana dashboards supported by Azure Data Explorer and Azure Data Factory for scalable observability.
Digital Graduate at Kongsberg Maritime
November 1, 2019 - September 7, 2025Participated in data science projects focusing on predictive maintenance and anomaly detection, contributing to deep learning-based engine monitoring initiatives and enhancing pipelines with data wrangling and cross-functional collaboration.
Digital Graduate at Rolls-Royce Commercial Marine
May 1, 2019 - September 7, 2025Visualized ship trajectory predictions using AIS and INS data with OpenCV, smopy, and folium. Predicted stationary vessels’ relative headings using image data to comply with COLREG, improving maritime safety and navigation accuracy. Modeled vessel trajectories based on AIS data with LSTM to support safety analyses.
Giant Leap Intern in AI at Vaisala
August 31, 2018 - September 7, 2025Created a contract-classifying program for locating legal documents in the company network, working with English and Finnish data, and utilizing NLP with OCR.
Data Scientist at Laerdal Medical
November 1, 2024 - PresentLead the end-to-end delivery of the company’s first AI-driven product, collaborating with Product, UX, Data, and SRE teams to translate unstructured business challenges into a well-defined AI engineering project, achieving a public demo within 3 months. Develop a modular evaluation framework that benchmarks every layer of the RAG stack (LLM, embeddings, vector index, prompt template, retrieval strategy) to surface the best-performing combinations. Transform a naïve RAG into an agentic RAG pipeline with evaluation-first multi-retrieval and self-reflection steps, emphasizing continuous improvement and practical deployment. Deploy and scale the service by containerizing with Docker, hosting on Azure App Service, automating CI/CD via GitHub Actions, and optimizing async I/O along with effective CPU/GPU and memory management. Maintain and enhance an internal employee chatbot with 500+ daily sessions, integrating advanced features such as agent-based planning and self-evaluation while sus
Data Scientist at Kongsberg Maritime
November 30, 2024 - September 7, 2025Designed and implemented a time-series anomaly detection system for vessel equipment using MLflow for automated model retraining; validated outputs led to significant client cost savings and helped secure additional departmental contracts. Leveraged Databricks to process and analyze large-scale datasets, developing, testing, and orchestrating over 30 automated daily data workflows to improve operational efficiency. Engineered predictive maintenance models to forecast equipment failures and assess cost impacts; conducted comparative fuel consumption analyses to highlight engine performance improvements. Developed a hybrid multiclass classification algorithm by integrating expert-defined rules with alarm signal data, combining time-series analytics and NLP to increase the accuracy and speed of alarm identification. Applied large language models to classify service reports, detect safety issues and non-conformities, and developed an RAG component to improve information extraction and enha
Digital Graduate at Kongsberg Maritime
November 30, 2019 - September 7, 2025Detected issues with engines using a Deep Learning-based anomaly detector.
Digital Graduate at Rolls-Royce Commercial Marine
May 31, 2019 - September 7, 2025Visualized ship trajectory predictions using AIS and INS data with tools like OpenCV, smopy, and folium. Predicted stationary vessels' relative headings using image data to comply with COLREG, improving maritime safety and navigation accuracy. Projected vessel trajectories based on AIS data using an LSTM, enhancing predictive accuracy and aiding in collision avoidance.
Giant Leap Intern in AI at Vaisala
August 31, 2018 - September 7, 2025Created a contract classifying program for locating legal documents in the company network, working with both English and Finnish, utilizing NLP with OCR.
Education
Master of Science at Aalto University
January 1, 2016 - January 1, 2021Bachelor of Science at Oklahoma State University
January 1, 2008 - January 1, 2012Master of Science, Machine Learning, Data Science, and Artificial Intelligence at Aalto University
January 11, 2030 - September 7, 2025Bachelor of Science, Management Information Systems at Oklahoma State University
January 1, 2008 - January 1, 2012Master of Science, Machine Learning, Data Science, and Artificial Intelligence at Aalto University
January 11, 2030 - September 7, 2025Bachelor of Science, Management Information Systems at Oklahoma State University
January 1, 2008 - January 1, 2012Master of Science, Machine Learning, Data Science, and Artificial Intelligence at Aalto University
January 11, 2030 - September 7, 2025Bachelor of Science, Management Information Systems at Oklahoma State University
January 1, 2008 - December 31, 2012Qualifications
Microsoft Certified: Azure AI Engineer Associate
January 1, 2025 - August 10, 2025Microsoft Certified: Azure Data Scientist Associate
January 1, 2023 - August 10, 2025Microsoft Certified: Azure AI Engineer Associate
January 1, 2025 - September 7, 2025Microsoft Certified: Azure Data Scientist Associate
January 1, 2023 - September 7, 2025Microsoft Certified: Azure Data Scientist Associate
January 1, 2023 - September 7, 2025Microsoft Certified: Azure AI Engineer Associate
January 1, 2025 - September 7, 2025Microsoft Certified: Azure AI Engineer Associate
January 1, 2025 - September 7, 2025Microsoft Certified: Azure Data Scientist Associate
January 1, 2023 - September 7, 2025Industry Experience
Healthcare, Manufacturing, Transportation & Logistics, Software & Internet, Energy & Utilities, Life Sciences, Professional Services, Media & Entertainment
Skills
Experience Level
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
Expert
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