Internship Data Specialist resume example

• Under supervision, defined the grain and refresh schedule of an analytics model, added SQL tests for duplicate business keys, and reconciled dashboard totals to the underlying transaction ledger.
• The team defined ownership, freshness, and validation for 42 decision-critical datasets; I supported research preparation, validation, and documentation under mentor review. The team kept the service stable through the next period of peak demand; confirmed with my mentor that my contribution was limited to the assigned support and validation work.
• The team analyzed 95,000 customer journeys and isolated three drivers of repeat use; 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, defined dbt data quality checks for eligibility date ranges, missing claim keys and reversed payments; added monitoring for failed checks and verified that quarantined records did not enter the published semantic layer.
• Under supervision, owned a claims-reporting reconciliation using SQL and dbt tests, resolved duplicate eligibility joins and completed the data-quality review before dashboard publication.
• Under supervision, published Tableau and Power BI metric definitions using reconciled source records, reduced weekly reporting queries by 30% and added monitoring for late adjustments.

• In a mentor-reviewed simulation, built SQL transformations for member eligibility and claims records, defining effective-date joins and the grain of each analytical table; checked that retroactive eligibility changes did not duplicate claim totals.
• As a second supervised exercise, reconciled analytical tables with source claims before publishing the Tableau report; traced a total mismatch to reversed claims and documented the approved treatment with the reporting owner.
• Under supervision, the team built a tested semantic layer for 27 recurring business metrics; 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.