Job Description

CATEGORIES: Other

DEPARTMENT: CEM Research Institute
Part-Time Cloud & Machine Learning Analyst


497583 Grand Forks, North Dakota, United States Part-time Staff Temporary Staff Closing on: Jan 30 2026

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Salary/Position Classification


$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
Purpose of Position



We are seeking a Cloud & Machine Learning Analyst to support cloud-based data analytics and machine learning initiatives. This temporary, part-time role will focus on analyzing data, supporting ML model development, and assisting with cloud infrastructure used for data processing and deployment



Duties & Responsibilities


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
Required Competencies


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
Minimum Requirements


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, TensorFlow, 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.



Preferred Qualifications


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 SageMaker, Azure ML, Google Vertex AI) Knowledge of containerization and orchestration (Docker, Kubernetes) Exposure to CI/CD pipelines and MLOps practices
To Apply



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.

Please note, all employment postings close at 11:55pm CST. Part-time/Temporary positions are posted for a minimum of 3 business days.

Other UND Career Openings


There are currently no jobs matching this criteria


Additional Information



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All information listed in this position announcement will be used by Human Resources, the Hiring Department, and EO/Title IX for screening, interviewing and selection purposes.


Need help?



Please email the Human Resources Department at UND.humanresources@UND.edu or contact us by phone at 701.777.4226. If you anticipate needing any type of accommodation to participate in any portion of the University's employment process, including completion of the online application process, please contact our office in advance of your participation or visit.


Veteran's Preference



Veterans claiming preference must submit all proof of eligibility by the closing date. Proof of eligibility includes a DD-214 or a copy of NGB 22 from National Guard or Reserve (with a unit located in ND) or certification from the applicant's unit command that the individual is expected to be discharged or released from active duty in the uniformed services under other than dishonorable conditions not later than one hundred twenty days after the date of the submission of the certification. If claiming disabled veteran status, proof of eligibility includes a DD-214 and a current letter of disability dated within the past year.


Confidentiality of Application Materials



Pursuant to NDCC 44-04-18.27, applications and any records related to the applications that identify an applicant are confidential, except records related to the finalists of the position, which are open to the public after the search committee has identified the top three or more finalists who will be invited to campus.


EEO Statement



The University of North Dakota is an equal opportunity employer (veteran/disability). All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristic. Veterans and individuals with disabilities are encouraged to apply.


Clery Statement



In compliance with the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act, the University of North Dakota publishes an Annual Security and Fire Safety Report. The report includes the university's policies, procedures, and programs concerning safety and security, as well as three years of crime statistics for our campus. As a prospective employee, you are entitled to a copy of this report. The report and statistical data can be found online at UND.edu. You may also request a paper copy of the report from the UND Police Department located at 3851 Campus Road, Grand Forks, ND, 58202.