Should I include academic or Kaggle projects on a Data Analyst resume?

If you have under two years of work experience, include 1–2 end-to-end projects that used messy real-world data, SQL queries, and a live dashboard link. Avoid generic Titanic or Iris tutorials.

Technology·Mid-Level·Reviewed 2026-10-20 by BioData PH Editorial Team

Data Analyst Resume Example & Writing Guide

Write a compelling Data Analyst resume that pairs SQL, Python, and BI dashboarding skills with real business decisions and revenue or cost impact.

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Devon Patel

Business & Data Analyst

devon.patel@example.com+1 512 555 0163Austin, TXlinkedin.com/in/devonpatel-exampledevonpatel-data.example.com

Summary

Analytical Business & Data Analyst with four years of experience transforming complex product and financial data into actionable recommendations. Proficient in SQL, Python, dbt, and Tableau, with a strong focus on cohort retention, experimentation, and self-service BI reporting.

Experience

Data Analyst, Veridian FinTech (Apr 2022 – Present)

Austin, TX

Modeled core revenue and user retention tables in Snowflake and dbt, cutting dashboard refresh times by 55%.
Designed executive Tableau suite tracking customer acquisition cost (CAC) and LTV across six acquisition channels.
Partnered with growth engineering to evaluate 18 A/B experiments using Python, improving onboarding completion by 9.4%.

Junior Operations Analyst, Sunbelt Supply Co. (Jul 2020 – Mar 2022)

Dallas, TX

Automated weekly inventory stockout alerts using SQL and Excel Power Query, reducing fulfillment delays by 16%.
Audited carrier freight invoices against contract rate tables, identifying $38K in billing overcharges.

Skills

SQL (PostgreSQL, Snowflake, BigQuery) · Python (pandas, NumPy, SciPy) · dbt · Tableau · Power BI · Excel (Power Query, PivotTables) · A/B Testing & Experimentation · Cohort & Funnel Analysis

Projects

Transit Punctuality Tracker, github.com/devonpatel-example/transit-analytics

Ingested public GTFS transit feeds into DuckDB and built an interactive dashboard analyzing route reliability by time of day.

Education

B.S. in Statistics & Economics, University of Texas at Austin (Aug 2016 – May 2020)

Austin, TX

Certifications

Tableau Desktop Specialist, Tableau (Sep 2022)

Languages

English (Native)

Key Takeaways

Highlight the business decisions your analyses unlocked, not just the charts you built.
Specify your core query, modeling, and visualization stack (SQL, Python, dbt, Tableau, Power BI, Looker).
Mention data hygiene, automated reporting, or self-serve dashboard adoption across stakeholders.

Relevant ATS Keywords for Data Analyst

Include terms below where they truthfully match your background and the target job posting:

SQLPythonTableauPower BISnowflakedbtCohort AnalysisA/B TestingData ModelingForecastingETL PipelinesExecutive Reporting

Reusable Bullet Point Examples

Built automated cohort retention models in SQL (Snowflake) and dbt, uncovering a churn driver that helped product teams recover $220K in annual revenue.
Replaced 14 manual weekly spreadsheets with self-service Power BI dashboards used by 90+ operations managers.
Analyzed A/B test results in Python (pandas, SciPy) for checkout pricing experiments across 300K sessions.
Standardized KPI definitions across finance and marketing, eliminating discrepancies in monthly board reporting.

Common Mistakes to Avoid

Listing Python or R without specifying what libraries or analytical methods you used.
Describing datasets without explaining the business recommendation that followed.

How to Write a Strong Data Analyst Resume

Frame dashboards around stakeholder action

Instead of 'Created Tableau dashboards for sales', write what metric the dashboard surfaced and how leadership used it to adjust pricing, inventory, or retention.

Include data pipeline and modeling context

Modern analytics teams value analysts who understand clean data modeling, SQL optimization, and version control.

Data Analyst Resume FAQs

Should I include academic or Kaggle projects on a Data Analyst resume?: If you have under two years of work experience, include 1–2 end-to-end projects that used messy real-world data, SQL queries, and a live dashboard link. Avoid generic Titanic or Iris tutorials.

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