Duy Khoa Nguyen

Developed and deployed robust machine learning models across diverse business units, achieving an average 15% improvement in prediction accuracy for key operational metrics.

Conducted in-depth data analysis and presented actionable insights to senior stakeholders, informing critical business strategies and contributing to a 10% reduction in data processing time.

Collaborated with cross-functional engineering and product teams to seamlessly integrate AI solutions, resulting in the successful launch of 3 new data-driven products within a year.

Optimized existing model architectures and data pipelines, enhancing system performance by 20% and ensuring scalability for increasing data volumes.

Researched and implemented cutting-edge AI techniques, including advanced deep learning architectures, to maintain competitive advantage and explore new solution avenues.

Designed and implemented scalable data pipelines using Python and SQL, reducing data ingestion and processing latency by 25% for critical analytical applications.

Built and fine-tuned predictive models for customer behavior and market trends, leading to a 5% increase in targeted marketing campaign effectiveness and improved ROI.

Performed rigorous A/B testing and comprehensive model performance evaluations, ensuring data integrity and optimizing model robustness by identifying key feature contributions.

Created interactive dashboards and detailed reports using Tableau and Power BI, enabling stakeholders to visualize complex data and make informed decisions faster.

Mentored a team of 3 junior data scientists, providing guidance on best practices in data cleaning, model development, and results interpretation, fostering team growth and project success.

Conducted in-depth research on state-of-the-art AI algorithms, including advancements in Natural Language Processing and Computer Vision, enhancing internal knowledge base.

Developed functional prototypes for novel AI-powered products, demonstrating feasibility and potential business value for future product lines.

Contributed to internal knowledge sharing initiatives, presenting research findings and methodologies to a team of 20+ AI engineers and data scientists.

Explored and evaluated new deep learning architectures and frameworks (e.g., PyTorch, TensorFlow), identifying optimal solutions for specific research challenges.

Assisted in the preparation of technical documentation and research reports, detailing experimental setups, results, and recommendations for further development.

Assisted senior data scientists in data cleaning and preprocessing for large datasets, ensuring data quality and readiness for model training.

Explored and applied various machine learning algorithms, including regression and classification models, to understand their practical applications.

Prepared comprehensive data reports and visualizations, supporting senior team members in project analysis and stakeholder communication.

Gained hands-on experience with industry-standard data science tools and methodologies, building a strong foundation for future roles.

Contributed to the development of preliminary data models, enhancing understanding of the full machine learning lifecycle.