Student Assistant - Data Science

In the role of Student Assistant – Data Science at ASU Enterprise Partners, you will contribute to the development and deployment of data science and AI solutions that create measurable business value. These may include analyses, predictive models, AI-enabled applications, automations, and other solutions designed to create business value. You will have the opportunity to explore new technologies and approaches, develop practical skills through hands-on experience, and make meaningful contributions to larger data science and AI initiatives with the support of experienced team members. 

Your work will focus on developing and supporting data science and AI solutions that create measurable business value. We strive to align assignments with each student's technical background and areas of interest while providing opportunities to build new skills through hands-on experience. Projects may involve activities such as developing and validating queries, evaluating AI-generated outputs, supporting predictive models and deployed solutions, improving analytical workflows, or contributing to other initiatives that advance organizational goals. 

Student employees are valued members of the Applied Data Science and Analytics (ADSA) team and have the opportunity to contribute to meaningful initiatives while expanding the technical and professional skills that support future careers in data science, analytics, artificial intelligence, and related fields. 

This position requires approximately 20 hours per week. This is a hybrid position, with an expectation that the student works approximately 12 of the 20 weekly hours on-site. 

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    Currently enrolled in a Bachelor's, Master's, or other graduate degree program at Arizona State University in a technical, quantitative, or analytical discipline, or a related field. Must have an expected graduation date of Fall 2027 or later. 

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    Has developed foundational knowledge and skills relevant to data science, analytics, software development, artificial intelligence, or related areas through coursework, projects, research, or practical experience. 

• Completion of an internship, research project, capstone, student organization project, or other hands-on experience involving data analysis, software development, artificial intelligence, analytics, automation, or related technical work. 

• Experience contributing to the development, testing, deployment, or support of technical solutions in academic, research, extracurricular, or professional settings.