High school teacher → data analyst at 7‑Eleven
Alex SanchezA math teacher and baseball coach who joined the Accelerator and landed a data role at 7‑Eleven about 50 days later.
Alex’s Data Roadmap
You’re the Collector.
You’ve gathered knowledge and learned the tools. Your skills are ahead of your portfolio. Now it’s time to turn them into a finished project that you can show and explain.
Your report card
Your starting point, based on your answers.
Skills
63 / 100
PortfolioStart here
15 / 100
Job readiness
20 / 100
Your scores come from your answers. They don’t compare you with other people. Job readiness covers your LinkedIn, résumé, and interviews.
Publish one portfolio project that someone can understand without opening your code.
One link introduces you and your projects. Each project opens to its own details: the question, images of your work, and your findings in a write-up or short video.
Your week-by-week roadmap
8 hours / weekLearn Excel, SQL, and Tableau while you build projects and prepare your job search. Publish early and improve as you go. You already know some tools: use those weeks to finish or improve existing projects rather than restart courses. You do not need a new project every week.
Take the time you need. This is a ten-week outline, but a week’s work can take longer. Skip things you already know. Pick projects that interest you, and finish one before piling on more.Your chosen goal: January 31, 2027.
Week 1
Set the foundation
- What to learn
- Explore data job titles: business, financial, marketing, product, and healthcare analyst. Choose a direction connected to your background and interests.
- What to build
- Choose one unfinished project worth completing. Write its question and outline the explanation you want a hiring manager to see.
- Finding work
- Refresh your LinkedIn photo, banner, headline, About, experience, skills, and education. Make room in Featured for your projects.
Week 2
Start showing your work
- What to learn
- Sharpen Excel with filters, formulas, pivot tables, and VLOOKUP. Practice the skills on your checklist using real data.
- What to build
- Build a small sales-data project. Show the question, your analysis, and what you found. Publish a simple first version on LinkedIn.
- Finding work
- Use LinkedIn actively: tell people what you are learning, share your work, and start conversations instead of treating your profile as a static résumé.
Week 3
Make data easy to understand
- What to learn
- Learn charts, color, and layout in Tableau. Connect a dataset and build a dashboard that answers a question.
- What to build
- Create an education-data project in Tableau, or improve the visual explanation of the project you already started.
- Finding work
- Update your résumé for your target role: relevant keywords, a clear job focus, and quantitative achievements where you have them.
Week 4
Put SQL to work
- What to learn
- Practice SELECT, FROM, WHERE, GROUP BY, and aggregations. Use queries to answer questions rather than only completing exercises.
- What to build
- Work through a financial-analysis question using SQL. Save your queries and explain what the results mean.
- Finding work
- Give your work a simple home on Carrd or GitHub Pages. Include an introduction and readable project details; link it from LinkedIn and your résumé.
Week 5
Go deeper and start reaching out
- What to learn
- Practice joins, UNION, CASE WHEN, and CTEs. Use the SQL checklist to identify what still needs practice.
- What to build
- Apply those techniques to a healthcare dataset, or extend an existing project with a more useful question.
- Finding work
- Start cold messages to recruiters, alumni, and peers. Begin a repeatable application routine; Avery’s sample target is 20 relevant applications a week when your schedule allows.
Week 6
Level up Tableau
- What to learn
- Practice heatmaps, treemaps, and stories in Tableau. Make the visual choices serve the question.
- What to build
- Build or extend a sports-data project and publish a short explanation of your findings.
- Finding work
- Keep applying and networking. Include local and hybrid opportunities that fit your goals, and share your project with people who might find it useful.
Week 7
Strengthen the skills you need
- What to learn
- Review Excel, SQL, and your visualization tool. Work on a gap that is slowing down a real project before adding another tool.
- What to build
- Try a manufacturing-data question, or finish an unfinished project using the tools you already know.
- Finding work
- If you have an interview booked, practice behavioral and technical questions and explaining your projects. Otherwise, keep applications and conversations moving.
Only if you need itIf the jobs you want ask for Python, try variables, loops, functions, pandas, and seaborn. Otherwise, leave it for later. You don’t need it just to start applying.
Week 8
Connect your work to an industry
- What to learn
- Practice explaining findings accurately. Explore correlation and regression when they are relevant to the question you are answering.
- What to build
- Use an HR dataset or a dataset from your target industry. Focus on a useful question and a clear recommendation.
- Finding work
- Keep engaging on LinkedIn with comments and posts. Talk about the kind of role you want and the work you can show.
Only if you need itAvery’s broader curriculum includes R, p-values, and regression. Explore these only when they support your target role; keep using your core tools otherwise.
Week 9
Polish your proof and widen the search
- What to learn
- Review the requirements in your target job descriptions. Close a repeated gap instead of collecting tools just in case.
- What to build
- Make your best projects easy to find and read. Add clear screenshots, a short write-up or video, and working links.
- Finding work
- Re-share projects and follow up with contacts. Avery’s broader plan increases to 40 applications a week; increase only if you can keep them relevant and maintain your networking.
Only if you need itExplore another BI tool or SAS only if the roles you want call for it. You do not need all of them to have a useful portfolio.
Week 10
Finish your capstone and keep going
- What to learn
- Bring your core tools together to answer a question in the industry you want to work in.
- What to build
- Finish your capstone, or improve your best existing project. Explain the question, your analysis, what you found, and what you’d recommend. Put it in your portfolio.
- Finding work
- Keep applying, posting, and networking. Review which efforts lead to conversations, improve your approach, and prepare for interviews as they arrive.
Keep applying and talking to people as you go. If you get an interview, make time to prepare for it right away. The plan gives you things to work on, but it can’t promise when you’ll get hired.
Your first three steps
- Choose one project to finish and write its main question in one sentence.
- Create a project page outline: question, approach, images, findings.
- Set aside your next work session to finish one part of that project.
What to leave for later. Pause collecting courses. For a data analyst goal, put Python and R aside while you focus on Excel, SQL, and one visualization tool.
Your skills checklist
Avery’s 51 skills, with your focus first.
Focus on Excel, SQL, and Tableau. Choose one visualization tool. Keep Python for later unless the roles you want specifically require it.
Check a skill when you can use it in your own work. These are your checkmarks, not an automatic assessment of mastery.
ExcelYour focus0/15
SQLYour focus0/16
Tableau / Power BIYour focus0/8
Practice these in Tableau. This is one shared set of eight skills; you do not need to learn both tools.
PythonFor later / when needed0/12
Checkmarks save in this browser for this roadmap. They do not change your report-card scores.
Help people find your work
Your portfolio
- Create one link that introduces you and your projects.
- Give each project its own detail page, with the question, approach, and findings.
- Use a readable write-up or short video, with images and text.
- Link to code where it helps; a recruiter should be able to understand your work without reading the repository.
Your résumé and LinkedIn
- Use a single-column résumé in Word or PDF, without tables or images.
- Use relevant keywords and describe achievements with numbers where you have them.
- Add a clear LinkedIn profile photo, a relevant headline, a cover photo, and a complete About section.
- Keep experience, skills, and education up to date, and make your portfolio easy to find.
Your network and applications
- List family, friends, neighbors, people from the pickup line or dog park. Start with people you already see.
- Tell them about your data journey and the work you want to do.
- Reach out to hiring managers and recruiters. Send a thoughtful cold message or arrange a coffee chat.
- Try different job websites and include conversations alongside applications.
Up to 25 applications without interviews is still a small sample. Keep going while improving how you present your work.
People who made the switch
Teacher → data analyst at Impossible Foods
Cindy CliffordAfter 25 years teaching around the world, she landed a remote data role at Impossible Foods.
Math teacher → analytics consultant at Wells Fargo
Courtney BallardAfter 10 years in the classroom, she started in late September and had her first data job offer that November.
Choir teacher → financial analyst at Humana
Mason RiceHe started the Accelerator in late October, applied within a week, and accepted a Humana offer through a referral in early December.
High school teacher → reimbursement analyst
Thomas GrescoA bootcamp got him no interviews. Posting on LinkedIn and messaging people directly got him a remote analyst job in less than 70 days.
1 / 5
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