About this role
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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