Student Intern

Key Responsibilities

• Collect, organize, clean, and validate data from multiple sources to ensure accuracy and completeness, including working with structured JSON data (e.g., API-based learning/event data).
• Develop recurring reports, dashboards, and visual summaries using tools such as Excel, Power BI, and SQL.
• Perform exploratory data analysis to identify trends, patterns, anomalies, and improvement opportunities across platform usage and completion data.
• Support the definition and tracking of key performance indicators aligned with business priorities.
• Document data sources, assumptions, methodology, findings, and limitations in a clear and reproducible way.
• Partner with business stakeholders to understand reporting needs and communicate insights in a simple, practical manner.
• Assist with process improvement initiatives by automating manual reporting tasks (Python scripting, Power Automate, or similar) where possible.
• Support light data engineering tasks such as API data pulls, JSON parsing/transformation, data validation scripts, and pipeline documentation for internal tools.

Required Qualifications

• Currently enrolled in a bachelor's degree program in Data Analytics, Data Science, Computer Science, Statistics, Mathematics, Engineering, Business Analytics, Information Systems, or a related field.
• Strong analytical mindset with attention to detail and the ability to work with structured data, including JSON.
• Working knowledge of Excel and familiarity with at least one analytics or visualization tool such as Power BI.
• Basic exposure to SQL or Python is a plus but not required (Python is especially useful given JSON/API data handling).
• Ability to communicate findings clearly to both technical and non-technical audiences.
• Curiosity, problem-solving skills, and willingness to learn new tools, processes, and business concepts.

Key Projects and Expected Deliverables

• Build a recurring dashboard consolidating usage and completion metrics across multiple systems, with a documented refresh process.
• Design and deliver a data quality checklist/validation script to flag inconsistencies or gaps across source systems.
• Support automation of at least one manual/recurring report, reducing turnaround time and manual effort.
• Produce a short KPI tracking framework document, defining metrics, data sources, and calculation logic for stakeholder review.
• Deliver a final presentation or write-up summarizing key findings, methodology, and recommendations from the internship.

Data Sources and Tools

• Enterprise platform data delivered via REST APIs, typically returned as JSON.
• Cloud-based data storage and processing (Azure).
• Excel, Power BI (or similar visualization tools), and SQL for reporting and analysis.
• Python for scripting, data cleaning, and automation tasks.
• Internal identity and directory data (e.g., Entra ID/Azure AD) for organizational context, where relevant.

Skills or Knowledge Areas the Intern Could Develop

• Practical experience working with real enterprise data pipelines and multi-source data integration.
• Hands-on exposure to API consumption and JSON data structures.
• Dashboard design and data storytelling for business stakeholders.
• Exposure to cloud data environments (Azure) and enterprise data governance practices.
• Fundamentals of process automation and reducing manual reporting overhead.
• Experience translating ambiguous business questions into structured analytical approaches.

Targeting students who will graduate in May 2028

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