Data Science Visualization Intern Gpu Performance - jobs at Nvidia in Vietnam, Hanoi

What you'll be doing:

• Data ETL & Engineering:Designing, building, and maintaining robust ETL (Extract, Transform, Load) pipelines to process and manage vast amounts of GPU performance data from diverse sources.

• Data Modeling:Developing flexible and scalable data models that can serve a wide variety of analytical and reporting needs, ensuring data integrity and efficiency.

• Data Visualization:Creating and managing dynamic, intuitive, and insightful dashboards in PowerBI. You will be responsible for translating complex data into clear visualizations that convey a clear narrative and support strategic decision-making.

• Data Mining & Insight Discovery:Applying statistical analysis and data mining techniques to our rich datasets. You will identify subtle patterns, pinpoint performance bottlenecks, and discover actionable insights that will inform future product development.

• Collaboration:Working closely with performance architects, engineers, and product managers to understand their requirements and deliver data-driven solutions.

What we need to see:

• Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Data Science, Business Analytics, Information Systems, or a related quantitative field.

• Strong foundational knowledge of database systems, data modeling, and ETL processes.

• Proficiency in SQL and at least one scripting language (Python preferred).

• Hands-on experience with a major BI/visualization tool (PowerBI is strongly preferred).

• A curious and proactive mindset. We are seeking individuals who demonstrate initiative, explore novel approaches, and assume responsibility for their project deliverables.

• Excellent problem-solving and communication skills.

Ways to stand out from the crowd:

• A demonstrated passion for data analysis and for discerning the underlying drivers of data trends.

• Familiarity with data analysis libraries in Python (e.g., Pandas, NumPy, Scikit-learn).

• A strong interest in or foundational knowledge of computer hardware, computer architecture, or GPU technology.

• Previous project or internship experience involving data analysis or visualization.