Software Developer I - Statistical Software & ML

Iowa State University; Ames (IA); On-site; USD 55,000 - 85,000; Full time

Job summary

Iowa State University’s Center for Survey Statistics and Methodology in Ames seeks a Software Developer I. You will develop software for the NRI survey and CSSM clients, involving statistical methods, estimation programs, database and web applications.

Preferred candidates hold a CS-related degree and have experience in higher education, NRI familiarity, and programming with machine learning and contrastive learning methods. This is a fixed-term position ending March 31, 2027.

Qualifications

• High school diploma or equivalent required.
• Bachelor's degree in computer science, computer engineering, mathematics, statistics, or related field preferred.
• Experience in higher education setting preferred.
• Knowledge or experience with NRI is a plus.
• Programming experience with machine learning and LLMs is desirable.
• Programming experience with contrastive learning methodology is desirable.

Responsibilities

• Develop software for the USDA-sponsored National Resources Inventory (NRI) survey and CSSM clients.
• Involve with software development using statistical methods and algorithms.
• Develop estimation programs with statistical sampling and imputation methods.
• Perform database programming and systems programming.
• Engage in web application programming.
• Collaborate with CSSM teams and external partners as needed.

Skills

ML programming

Contrastive learning

Higher education experience

NRI knowledge

Education

High school diploma or equivalent

Bachelor's degree in computer science / related field

Job description

Iowa State University’s Center for Survey Statistics and Methodology in Ames seeks a Software Developer I. You will develop software for the NRI survey and CSSM clients, involving statistical methods, estimation programs, database and web applications.

Preferred candidates hold a CS-related degree and have experience in higher education, NRI familiarity, and programming with machine learning and contrastive learning methods. This is a fixed-term position ending March 31, 2027.