Student Assistant – Data Science

ASU Enterprise Partners•Scottsdale, AZ

9d•Hybrid

About The Position

As a Student Assistant – Data Science at ASU Enterprise Partners, you will contribute to the development and deployment of data science and AI solutions intended to create measurable business value. Solutions may include analyses, predictive models, AI-enabled applications, automations, and related work. Assignments are aligned with students’ technical backgrounds and interests while providing opportunities to develop practical skills through hands-on experience and contribute to broader data science and AI initiatives with support from experienced team members. Work may include developing and validating queries, evaluating AI-generated outputs, supporting predictive models and deployed solutions, improving analytical workflows, and advancing other organizational initiatives. Student employees are members of the Applied Data Science and Analytics (ADSA) team and contribute to meaningful projects while building technical and professional skills for careers in data science, analytics, artificial intelligence, and related fields. The position requires approximately 20 hours per week. It is hybrid, with an expectation that approximately 12 of those weekly hours are worked on-site.

Requirements

Currently enrolled in a bachelor's, master's, or other graduate degree program at Arizona State University in a technical, quantitative, analytical, or related field.
Expected graduation date of Fall 2027 or later.
Foundational knowledge and skills relevant to data science, analytics, software development, artificial intelligence, or related areas, developed through coursework, projects, research, or practical experience.
Experience with Python, SQL, and other data analysis or technical tools commonly used in data science, analytics, software development, or artificial intelligence.
Ability to evaluate information, break down complex problems, and contribute to data-driven and technology-enabled solutions.
Curiosity, critical thinking, and willingness to learn new concepts, tools, and approaches.
Comfort working with data and applying quantitative or computational methods to practical problems.
Interest in exploring and applying emerging technologies, methodologies, and tools in support of business objectives.
Ability to communicate technical concepts, progress, findings, and recommendations clearly to technical and non-technical audiences.
Willingness to work effectively as part of a team, contribute to shared goals, and engage constructively with feedback.
Ability to work across varied projects and responsibilities while balancing competing priorities and evolving requirements.

Nice To Haves

Completion of an internship or project-based experience in a relevant area such as data science, data analytics, data engineering, or machine learning engineering.
Experience deploying data solutions, preferably using Google Cloud Platform (GCP), Amazon Web Services (AWS), or Microsoft Azure.
Exposure to programming, data analysis, cloud technologies, artificial intelligence, automation, or related technical disciplines through coursework, projects, research, internships, or personal initiatives.
Familiarity with structured or unstructured data for analysis, reporting, decision-making, or solution development.
Exposure to Google Analytics (GA4).
Exposure to modern artificial intelligence concepts, tools, or applications and interest in their practical use.
Familiarity with cloud-based or distributed computing environments and understanding of how technology components can be integrated to support scalable solutions.
Experience with Google Cloud Platform (GCP) and BigQuery.
Interest in designing, building, testing, and continuously improving technical solutions that create measurable value.
Demonstrated enthusiasm for learning new technologies, methodologies, and approaches and applying them to evolving business challenges.

Responsibilities

Contribute to the development, testing, and refinement of data science, analytics, automation, and AI solutions that support business objectives.
Assist with data analysis, solution testing, validation, and evaluation.
Support the design and implementation of data-driven and AI-enabled solutions.
Assist with deploying, integrating, testing, and maintaining solutions.
Collaborate with the Applied Data Science and Analytics team and other stakeholders to support organizational objectives.
Use modern data, analytics, cloud, and AI technologies to develop, evaluate, and support solutions.
Help evaluate solution performance and contribute to ongoing improvements based on business needs, feedback, and evolving technologies.
Communicate progress, results, technical concepts, and recommendations clearly to team members and stakeholders.