Part-Time Cloud & Machine Learning Analyst

Job no: 497583

Work type:
Part-time Staff, Temporary Staff

Location:

Grand Forks

Categories:
Other

• $25.00 hourly, Non-Exempt (Eligible for overtime)
• 15-20 hours per week
• 100% Remote Work Availability:
  No
• Hybrid Work Availability (requires some time on campus):
  No

• Analyze large datasets (Aviation or Energy) using cloud-based tools and platforms
• Support development, training, testing, and evaluation of machine learning models
• Perform data preprocessing, feature engineering, and validation in cloud environments
• Assist with deploying and monitoring ML models on cloud platforms
• Work with cloud storage, compute, and data pipelines (e.g., data lakes, ETL workflows)
• Support cost optimization, performance tuning, and basic cloud security best practices
• Collaborate with data scientists, cloud engineers, and business stakeholders
• Create documentation, dashboards, and analytical reports
• Strong analytical and problem-solving skills
• Ability to communicate technical findings to non-technical stakeholders
• Experience working in agile or fast-paced environments
• Good documentation and organizational skills
• Bachelor’s degree in Computer Science, Data Science, Engineering, or related field
• Hands-on experience with at least one cloud platform (AWS, Azure, or GCP)
• Experience using Python for data analysis and machine learning
• Familiarity with ML frameworks (e.g., scikit-learn, Tensor Flow, PyTorch)
• Basic knowledge of SQL and data modeling
• Successful completion of a Criminal History Background Check

In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the US and to complete the required employment eligibility verification form upon hire. This position does not support visa sponsorship for continued employment.

• Master’s degree (MS) preferred in Computer Science, Data Science, Machine Learning, AI, Cloud Computing, or related field
• Experience with cloud-native ML services (e.g., AWS Sage Maker, Azure ML, Google Vertex AI)
• Knowledge of containerization and orchestration (Docker, Kubernetes)
• Exposure to CI/CD pipelines and MLOps practices

For consideration and a successful screening, please include a cover letter and resume outlining how you meet the requirements of the position along with your application.

Advertised: 15 Jan 2026 Central Standard Time
Applications close: 30 Jan 2026 Central Standard Time