Sofia Herrera: Analytics Intern
Sofia's resume leans on one internship, a research job and a public project because that is what most new analysts have. Every bullet shows a real dataset and a person who used the output. Her Google certificate sits in its own line rather than at the top, since the internship work is stronger proof of skill than the credential.
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Sofia Herrera · Phoenix, AZ · sofia.herrera@email.example · (602) 555-0119
Summary
Economics graduate and former analytics intern who writes clean SQL, builds Tableau dashboards people actually open and explains findings in plain language. Strongest with retail and operations data. Looking for a junior analyst role with real data volume and a senior analyst to learn modeling habits from.
Experience
Analytics Intern, Saguaro Home Goods · Phoenix, AZ · May 2025 — Aug 2025
- Wrote SQL queries joining point-of-sale and inventory tables to flag 340 items that sold out every weekend across 22 stores, shared with the replenishment team.
- Rebuilt the weekly store performance report as a Tableau dashboard, replacing a manual Excel file that took the team lead four hours each Monday.
- Cleaned three years of returns data in pandas, standardizing reason codes so the merchandising team could compare return causes by category for the first time.
Research Assistant, Economics Department, Desert Valley University · Tempe, AZ · Sep 2024 — Apr 2026
- Assembled and documented a county-level housing dataset from public sources, writing reproducible R scripts that a professor reused in two published working papers.
- Ran regression analyses on rent and commute data and summarized results in short memos for a faculty research group.
Projects
City Bike Demand Analysis
- Analyzed 1.2 million public bike-share trips in SQL and Python, then published a Tableau Public story showing station shortages by hour and weather.
Education
BA, Economics, minor in Statistics, Desert Valley University (2026)
Certifications
Google Data Analytics Professional Certificate
Skills
SQL, Excel (pivot tables, XLOOKUP), Tableau, Python (pandas), PostgreSQL, Google Sheets, Descriptive statistics, Data cleaning, Jupyter, Presentation of findings
Kevin Tran: Data Analyst
Kevin is in Canada and works in a modern stack, so dbt, Snowflake and Looker appear inside his bullets, not just in the skills block. The theme across his jobs is trust in numbers: one churn definition, data quality tests, reconciled totals. That theme is what makes a mid-level analyst worth a raise over a junior.
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Kevin Tran · Vancouver, BC · kevin.tran@email.example · (604) 555-0172
Summary
Data analyst with five years in e-commerce and subscription analytics, working in SQL, dbt and Looker on Snowflake. Turns vague questions from marketing and product into clear metrics, tested hypotheses and dashboards with defined owners. Known for fixing metric definitions so leadership trusts the numbers.
Experience
Data Analyst, Coastline Outfitters Online · Vancouver, BC · Feb 2023 — Present
- Built dbt models and a Looker explore for subscription retention, giving marketing a single definition of churn after three teams had reported three different numbers.
- Analyzed 14 checkout A/B tests with product managers, recommending two changes that together raised conversion on mobile by about 3%.
- Created a cohort dashboard showing repeat purchase by acquisition channel, which led marketing to shift budget away from two paid channels with low second orders.
- Added automated data quality tests in dbt for 25 core tables, catching broken source loads before they reached Monday executive reports.
Junior Data Analyst, Fraserview Insurance Brokers · Burnaby, BC · Jun 2021 — Jan 2023
- Automated monthly policy renewal reporting with SQL and Python, cutting preparation time from two days to two hours for the operations manager.
- Built a Power BI dashboard for claims turnaround by adjuster and region, used by supervisors in weekly workload meetings.
- Investigated a gap between finance and operations premium totals, tracing it to duplicated endorsements and documenting the fix with the data team.
Education
BBA, Business Analytics, Pacific Shore University (2021)
Certifications
Microsoft Certified: Power BI Data Analyst Associate
Skills
SQL, Snowflake, dbt, Looker, Python (pandas, statsmodels), A/B test analysis, Cohort and retention analysis, Excel, Data modeling, Git, Stakeholder interviews, Data quality checks
Rebecca Lindqvist: Senior Data Analyst
Rebecca's sample shows a senior analyst who leads without leaving analysis behind. Her bullets mix team leadership, forecasting, experiment design and platform migration, each tied to an operational decision. Her oldest role is cut to two short bullets, and the MS in statistics supports the forecasting claims.
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Rebecca Lindqvist · Minneapolis, MN · rebecca.lindqvist@email.example · (612) 555-0134
Summary
Senior data analyst with 11 years in healthcare and retail analytics, leading metric design, forecasting and self-serve reporting for operations leaders. Sets analytics standards, mentors analysts and partners with data engineering on modeling. Comfortable presenting trade-offs to executives without hiding uncertainty in the numbers.
Experience
Senior Data Analyst, Northstar Community Health Network · Minneapolis, MN · Aug 2020 — Present
- Lead a team of four analysts supporting clinic operations, owning the metric catalog that defines visit volume, no-shows and capacity for 38 clinics.
- Built a weekly appointment demand forecast in Python, now used by scheduling to set staffing levels and credited with reducing overtime hours by about 10%.
- Partnered with data engineering to move reporting from spreadsheets to BigQuery and Tableau, retiring 60 manual reports and giving managers self-serve views.
- Designed a no-show reminder experiment with the patient access team, measuring a reduction in missed appointments that justified a network-wide rollout.
Data Analyst, Lakewood Grocery Cooperative · St. Paul, MN · Mar 2016 — Jul 2020
- Developed store-level sales and margin dashboards in Tableau for 45 stores, replacing static PDF reports with filters by region, category and promotion.
- Analyzed promotion lift with SQL and R, showing that several recurring discounts cannibalized full-price sales and helping merchandising redesign the promo calendar.
- Trained 30 store and category managers on reading the dashboards, cutting ad hoc report requests to the analytics team in half.
Reporting Analyst, Twin Rivers Logistics · Minneapolis, MN · Jun 2014 — Feb 2016
- Produced daily on-time delivery and carrier performance reports in SQL and Excel for the transportation team.
- Built an Access-to-SQL Server migration plan for legacy reports, documenting every calculation before the old database was retired.
Education
MS, Applied Statistics, Great Lakes Technological University (2014)
BA, Mathematics, Prairie Hill College (2012)
Certifications
Tableau Certified Data Analyst
Skills
SQL, Python, R, Tableau, Power BI, BigQuery, dbt, Time-series forecasting, Experiment design, Metric definition, Data governance, Mentoring analysts, Executive presentations
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How to write each section of a data analyst resume
Header and portfolio link
Add a portfolio link next to your email and LinkedIn: a Tableau Public profile, a GitHub repository with notebooks, or a short personal site. Pick the two strongest pieces and make sure each has a one-paragraph explanation of the question, the data and the answer.
If your portfolio uses public datasets, say so. Never publish an employer's real data, even anonymized, unless you have written permission.
Summary
Lead with your domain and analytical focus, such as marketing analytics, healthcare operations or financial reporting, then name your core stack. Domain matters more than many candidates expect, because an analyst who already knows claims data or subscription metrics needs less ramp-up.
Avoid generic phrases about being data-driven. Every analyst is; say what kind of decisions your work has supported.
Experience
Write bullets in the order question, method, result. The question can be implied, but the method should name a tool or technique and the result should name a decision, a time saving or a business metric. Include volumes when they are meaningful: rows, stores, customers, reports retired.
Show depth of SQL by mentioning window functions, CTEs or performance tuning only where they mattered to the result. Interviewers will test you on anything you claim, so keep it honest.
Skills
Split skills into querying and storage, analysis and statistics, and visualization. Name the specific BI tool and warehouse you used, because many postings filter on Power BI versus Tableau or Snowflake versus BigQuery. Excel still matters for many analyst jobs, so list advanced features rather than just the word Excel.
If you are learning Python or R, list it only after you have used it on at least one project you can talk through.
Education and certifications
Degrees in statistics, economics, math, computer science or business analytics are common, but plenty of analysts come from other fields. If yours is unrelated, add relevant courses or a certificate and let your projects carry the case.
Vendor certifications such as the Power BI or Tableau analyst exams are worth listing when the posting names that tool. Entry-level certificates help career changers most; experienced analysts can drop them once real work speaks for itself.
Data Analyst resume summary examples
Entry-level objective: Statistics graduate seeking an entry-level data analyst role on an operations or retail team. Brings strong SQL, Tableau and Excel skills, a public bike-share analysis project and experience presenting findings to non-technical audiences in class consulting projects.
It names the target team and tools, then points to a project the reader can open, which makes a no-experience objective concrete.
New-grad summary: Analyst with an economics degree and a retail analytics internship, writing SQL against sales and inventory data and turning it into Tableau dashboards used weekly. Comfortable cleaning messy data in pandas and explaining results in short written summaries.
It presents the internship as real work with real users, which is more persuasive than listing coursework.
Mid-level summary: Data analyst with five years in e-commerce, specializing in retention, experimentation and metric definitions in SQL, dbt and Looker. Partners with marketing and product to frame questions, test changes and retire conflicting reports so teams work from one set of numbers.
Domain plus analytical specialty plus stack lets a hiring manager place the candidate in seconds.
Senior summary: Senior data analyst with 11 years in healthcare and retail, leading forecasting, experiment design and self-serve reporting. Manages a small analyst team, owns metric governance and presents trade-offs to executives with honest confidence ranges.
It shows leadership and governance scope while keeping forecasting and experimentation as hands-on skills.
Data Analyst resume bullet examples: weak vs strong
The strong versions use made-up figures for a fictional candidate. Replace them with your own real numbers, or describe the scope (team size, volume, frequency) if you have none.
Shows the data sources, the finding and the action, which is the whole point of a query.
Time saved and named users prove the dashboard is alive, not abandoned after launch.
Mentioning power checks shows statistical judgment, not just reading a dashboard result.
Moves data quality from a chore to a prevented business problem.
Resolving definitions is senior-level work; the strong version makes that visible.
Names the method, the user of the forecast and a modest, believable outcome.
Specific before and after time is the clearest proof of automation value.
Presentation bullets need a decision at the end, or they read as attendance.
Keywords from live data analyst job postings
We read 124 live data analyst postings (44 US and 80 Canadian) from our job feed on October 14, 2026 and counted how many mention each skill, tool or credential. A posting counts once per term, wherever it appears in the title or description. Use the list to check your resume for gaps that are real for you, not as a checklist. For grouped lists with placement tips, see the data analyst resume keywords guide.
| Keyword | Postings | |
|---|---|---|
| SQL | 93 of 124 (75%) | |
| Dashboards | 77 of 124 (62%) | |
| Stakeholders | 75 of 124 (60%) | |
| Python | 63 of 124 (51%) | |
| Power BI | 60 of 124 (48%) | |
| Excel | 52 of 124 (42%) | |
| Tableau | 51 of 124 (41%) | |
| Statistics | 49 of 124 (40%) | |
| Data quality | 37 of 124 (30%) | |
| Data visualization | 32 of 124 (26%) | |
| Data modeling | 30 of 124 (24%) | |
| KPIs | 20 of 124 (16%) | |
| Data governance | 19 of 124 (15%) | |
| Snowflake | 18 of 124 (15%) | |
| Azure | 17 of 124 (14%) | |
| R | 15 of 124 (12%) | |
| Looker | 15 of 124 (12%) | |
| ETL | 13 of 124 (10%) | |
| Forecasting | 13 of 124 (10%) | |
| pandas | 10 of 124 (8%) | |
| AWS | 9 of 124 (7%) | |
| Machine learning | 9 of 124 (7%) |
Source: 124 unique postings whose title matches the role, from the WhatJobs publisher feed (US and Canada), collected October 14, 2026. Duplicate reposts were counted once. Counts change daily; a term not listed may still matter for a specific employer.
Skills for a data analyst resume
Querying and data platforms
- SQL
- PostgreSQL
- Snowflake
- BigQuery
- Redshift
- dbt
SQL is close to universal for this job; name the warehouse to match the posting.
Analysis and statistics
- Python (pandas)
- R
- Excel
- A/B testing
- Regression
- Forecasting
- Cohort analysis
List methods you applied at work, and show one of them in a bullet.
Visualization and BI
- Tableau
- Power BI
- Looker
- Looker Studio
- Excel charts
Mention who used your dashboards and how often to prove adoption.
Data management
- Data cleaning
- Data modeling
- Data quality testing
- Documentation
- Git
These separate analysts others trust from analysts whose numbers get second-guessed.
Soft skills, and how to prove them
- Framing questions: Show a bullet where you turned a vague request into a specific metric or test before building anything.
- Data storytelling: Name a presentation or memo and the decision leaders made after seeing it.
- Skepticism: Describe a discrepancy you investigated, such as two systems disagreeing, and what you found.
- Teaching others: Mention dashboard training sessions or documentation you wrote, and the drop in repetitive requests that followed.
- Prioritization: Show how you handled competing requests, for example by building a self-serve tool instead of answering each one by hand.
Certifications and licenses
- Microsoft Certified: Power BI Data Analyst Associate (Microsoft): Exam PL-300; directly relevant when postings ask for Power BI and DAX.
- Tableau Certified Data Analyst (Tableau (Salesforce)): Shows hands-on Tableau skill; most valuable at Tableau-heavy employers.
- Google Data Analytics Professional Certificate (Google (via Coursera)): Entry-level program covering spreadsheets, SQL, Tableau and R; useful for career changers without a related degree.
- SAS Certified Specialist: Base Programming (SAS Institute): Still requested in some banking, insurance, pharma and government analytics teams that run SAS.
Looking for low-cost options? See our list of free certifications in this field.
US vs Canada: data analyst resumes and pay
United States
Data analyst is an unregulated title in the US, and titles vary a lot: business intelligence analyst, reporting analyst and analytics specialist often describe the same job. Mirror the posting's title in your summary if your work matches. Healthcare roles may expect familiarity with HIPAA, finance roles with SOX reporting controls, and federal or defense roles may require citizenship or a clearance. Do not include a photo, birth date or Social Security number. Keep US letter page size when you export.
The BLS does not publish a separate occupation for data analysts, so we show no US wage figure rather than borrow a different job's numbers.
Canada
In Canada the title is also unregulated, and federal government analyst roles often appear under classifications such as EC or CS, with bilingual English and French requirements for many positions. Analysts working with personal data should know PIPEDA or provincial privacy laws, and Quebec roles may require French and familiarity with Law 25. Co-op placements are common on Canadian new-grad resumes and should be listed as experience. Mention work permit status when it applies; skip photos and personal details.
| Job Bank occupation | Low | Median | High |
|---|---|---|---|
| Data Analyst - Informatics And Systems (NOC 21223) | $25.00/h | $40.87/h | $61.03/h |
Canada-wide wages in CAD, Job Bank (Government of Canada), reference period 2023-2024. Provincial figures differ; follow the link for your province.
Check your data analyst resume before you apply
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FAQ
What should a data analyst resume include if I have no experience?
Lead with two strong projects using real public data, a short summary naming your tools, and any internship, research or volunteer work involving numbers. Link a portfolio where each project explains the question, the method and what you found. Coursework helps only if it matches the job, such as statistics or databases.
Is Python required on a data analyst resume?
Not always. Many analyst postings focus on SQL, Excel and a BI tool, and treat Python or R as a plus. If you know Python, show it in a bullet about cleaning, automation or analysis. If you do not, strong SQL and dashboard work will still qualify you for many roles.
How do I show impact as an analyst when I don't own the decision?
Describe the decision your analysis informed and who made it, such as merchandising changing a promo calendar or scheduling adjusting staffing. You do not need to claim the result as yours alone. Showing that your work was used is the impact.
Should I list Excel if I know SQL and Python?
Yes, if the posting mentions it, and many do. List specific capabilities like pivot tables, XLOOKUP, Power Query or financial modeling so it reads as advanced use rather than basic familiarity. Hiring managers in finance and operations still rely heavily on spreadsheets.
What's the difference between a data analyst and data scientist resume?
A data analyst resume centers on SQL, reporting, dashboards, experiments and business decisions. A data scientist resume puts more weight on predictive modeling, machine learning, deployment and statistics depth. If you are moving toward data science, add modeling projects but keep your analyst impact visible.