I’m Nhat Nguyen, a data analyst who turns messy datasets into clean, trustworthy insights that leaders can act on. I design KPI frameworks, build interactive dashboards, and automate reporting so teams spend less time pulling numbers and more time making decisions. From raw data to crisp storytelling, I ship practical solutions with SQL, Python, Power BI, and Tableau.
Owned KPI reporting end-to-end—partnered with stakeholders to define metrics, modeled clean datasets, and delivered executive-ready dashboards that improved visibility into performance and accelerated decision-making.
Supported senior analysts by cleaning and validating data, building repeatable ETL workflows, and producing clear visualizations and ad-hoc analyses to answer urgent business questions.
Built a strong foundation in systems and analytics—statistics, data structures, and applied machine learning—with hands-on projects focused on data cleaning, visualization, and practical problem-solving.
KPI dashboard simulating sales by category, region, and segment with drill-downs.
Monthly delay percentages by carrier with seasonal worst-month insights. Click a carrier for details.
CSV normalization (dates, categories, duplicates) with a raw vs cleaned preview.
What I can do across Data Analytics, AI/ML, and Software Engineering—from raw data to shipped, reliable solutions.
Business-ready insights through KPI design, analytics workflows, and executive dashboards.
Production-minded ML pipelines with strong evaluation, interpretability, and real-world impact.
Reliable, maintainable systems and automation that power scalable data products.
Make data consistent, scalable, and ready for analytics & AI.
Tools I use to build dashboards, automate analysis, and collaborate.
Comfortable with core cloud concepts and shipping small projects.
Developing machine learning models for early disease detection using medical imaging and patient data, assisting doctors in accurate diagnoses.
Using time-series analysis and reinforcement learning to predict patient recovery trajectories and optimize treatment plans.
Leveraging generative AI and molecular modeling to accelerate drug development, reducing time and cost for new therapies.
Implementing AI for resource allocation, patient flow optimization, and predictive maintenance of medical equipment.
Creating conversational AI systems for patient triage, appointment scheduling, and continuous health monitoring.
Developing frameworks for bias detection, explainable AI models, and ensuring equitable healthcare delivery.
Own KPIs, build executive dashboards, and communicate insights to drive product and revenue decisions.
Design reliable data models, optimize queries, and automate repeatable analysis with clean, tested code.
Use AI to accelerate exploration and storytelling while keeping rigorous, human-checked conclusions.