Internship Data Analyst resume example

• Under supervision, documented the denominator and exclusion rules for conversion metrics, investigated differences between SQL extracts and the dashboard, and shared cohort-level findings with the business owner.
• The team reconciled revenue definitions across finance, sales, and product tables; I supported research preparation, validation, and documentation under mentor review. The team removed a recurring quality failure from the reviewed workflow; confirmed with my mentor that my contribution was limited to the assigned support and validation work.
• The team analyzed 160,000 onboarding sessions and isolated three abandonment drivers; I supported research preparation, validation, and documentation under mentor review. The team sustained the adoption gain after rollout; confirmed with my mentor that my contribution was limited to the assigned support and validation work.
• Under supervision, owned Tableau data-quality checks using reconciled source totals, resolved duplicate customer records and released a dashboard with explicit denominator definitions.
• Under supervision, redesigned a weekly visualization using stakeholder task tests, reduced time to locate an outlier from 6 to 2 minutes and documented the excluded populations.

• In a mentor-reviewed simulation, used SQL and Python for data analysis of service requests, checking duplicates, missing timestamps, and category changes; resolved data quality issues before comparing turnaround time across teams.
• As a second supervised exercise, created a Tableau visualization with documented denominators and drill-down views; reconciled its totals against a Power BI reference report and explained differences caused by refresh timing.
• Under supervision, the team built a governed weekly operating dashboard for 14 leaders; I supported research preparation, validation, and documentation under mentor review
• Generated synthetic source records with duplicates, late arrivals and corrected values; wrote assertions for row counts and key uniqueness, and recorded the expected effect of each case on the reported metric.
• Compared the analytical output with a manually calculated reference table, traced differences to a transformation step, and retained a data dictionary and rerun instructions alongside the corrected query.
• Owned the synthetic-data validation using a manually calculated reference, resolved duplicate-key inflation and completed a notebook that reproduces the corrected totals.

Relevant coursework: Algorithms, operating systems, databases, computer networks

• Published an independent methods note using reproducible queries, explaining the data grain, excluded records and sensitivity of the result to a changed denominator.