Student Assistant – Business Intelligence

Student Assistant – Business Intelligence

The Student Assistant – Business Intelligence will support key initiatives within the Data Analytics & Insights (DAI) Business Intelligence (BI) team at ASU Enterprise Partners (ASUEP). The DAI BI team oversees analytics, reporting, and data‑driven decision support across the organization. This role will assist with data analysis, reporting, dashboard development, data preparation, and project‑based work, contributing to real business initiatives and helping translate data into insights that inform strategy and operations.

Depending on project needs, the student may support agile, continuous delivery, and project activities.

The position requires approximately 15–20 hours per week, with additional availability during school breaks.

• Takes responsibility for supporting assigned projects from initiation through completion, under the guidance of team leads
• Performs data analysis and reporting to track key metrics, identify trends, and support decision‑making for DAI BI leadership and partner teams.
• Gathers, cleans, and consolidates data from multiple sources and stakeholders to support reporting, analysis, and downstream use.
• Assists in developing and improving processes for aggregating, transforming, and analyzing data, including working with large or complex datasets.
• Creates, designs, and builds reports, dashboards, presentations, and visualizations (e.g., graphs, tables, charts) to clearly communicate data findings.
• Supports data validation, documentation, and basic data flow or process mapping.
• Provides additional analytical, reporting, or project support to the DAI BI team as needed.
• Performs other duties and projects as assigned.

• Excellent analytical, problem‑solving, and decision‑making skills.
• Highly motivated and self‑driven, with a strong willingness to learn and develop new skills.
• Ability to take initiative, set priorities, and remain flexible.
• Familiarity with data visualization tools (e.g., Power BI, Looker Studio, Tableau, Micro Strategy).
• Working knowledge of SQL, including writing and understanding queries across moderately large datasets.
• Exposure to data preparation, validation, or transformation concepts with high attention to accuracy.
• Strong critical‑thinking skills and attention to detail.
• Ability to perform accurate data validation and transformation.
• Ability to organize, document, and clearly explain analytical or data‑related work.
• Strong organizational skills with the ability to handle multiple projects.
• Motivated, adaptable, and eager to learn new tools, technologies, and business concepts.
• Collaborative working style with the ability to function effectively in a team‑based environment.
• Strong interpersonal and communication skills, including the ability to interact with senior leaders.
• Ability to work effectively both independently and collaboratively.
• Ability to maintain a high degree of confidentiality regarding information related to Enterprise Partners, its subsidiaries, University business, and confidential prospect information.
• Team‑oriented strategist capable of managing complex situations involving multiple stakeholders.
• Ability to represent the organization professionally.
• Proficiency with Microsoft Office Suite (PowerPoint, Word, Excel), including creating pivot tables and visualizing data.
• Alignment with ASU’s vision as the New American University.
• Ability to navigate complex environments with evolving priorities and communication plans.

• A current undergraduate or graduate student at Arizona State University pursuing a degree in Computer Science, Data Analytics, Business Intelligence, Statistics, Mathematics, or a related field.
• Willingness to learn and ability to work well with others.
• Must be willing to sign and abide by a confidentiality agreement.

• Current undergraduate student at Arizona State University pursuing a degree in Computer Science, Data Analytics, Business Intelligence, Statistics, Mathematics, or a related field.
• Exposure to data engineering concepts, reporting systems, or analytics pipelines through coursework, projects, or internships.
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