Student

This is a fully remote position, open to applicants in Tennessee.

📋 Description

• Enhance rule-based logic for real-time tagging of jobs utilizing job metadata and runtime characteristics.

• Design and implement strategies for the automated extraction of storage locations from job metadata.

• Introduce and assess both supervised and unsupervised classification models to refine workload categorization.

• Collaborate with team members to integrate visualization of classifications into existing dashboard platforms.

• Document processes, insights, and enhancements for internal knowledge sharing and future developments.

⛳️ Requirements

• Currently pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related discipline.

• Familiarity with Python and data processing libraries, including Pandas and NumPy.

• Understanding of fundamental machine learning concepts and classification methodologies.

• Experience with both structured and unstructured data.

• Strong analytical abilities and problem-solving skills.

• Capacity to work independently while effectively communicating within a team environment.

• Preferred experience with job schedulers like LSF, Slurm, or PBS, as well as HPC environments.

• Knowledge of metadata parsing and log analysis is preferred.

• Familiarity with data visualization tools such as Plotly, Dash, or Grafana is preferred.

• Experience with dashboard integration and web-based UI frameworks is preferred.

• Prior experience with rule-based systems or workflow automation is preferred.

🏝️ Benefits

• Gain hands-on experience in a high-performance computing environment.

• Opportunity to make contributions to valuable infrastructure and analytics tools.

• Receive mentorship from seasoned professionals in HPC and data science.

• Enjoy a flexible schedule that accommodates academic commitments.