A complete, annotated resume for an early-career data analyst. Every section is broken down — so you can see exactly what turns 1.5 years of experience into interview callbacks.
Scroll down to see the full resume, then read why each section works.
Data analyst with 1.5 years of experience translating business questions into actionable data insights. Currently at HubSpot, where I built a churn prediction dashboard that identified 340 at-risk accounts and directly informed the retention team’s Q3 strategy. Self-taught in SQL and Python with a background in economics that keeps my analysis grounded in business context, not just numbers.
Analysis: SQL (PostgreSQL, BigQuery), Python (pandas, matplotlib), Excel (pivot tables, VLOOKUP, Power Query) Visualization: Tableau, Looker, Google Data Studio Other: Google Analytics, A/B testing, cohort analysis, Git
Seven things this junior data analyst resume does that most early-career resumes don’t.
Maya doesn’t open with “proficient in SQL and Tableau.” She opens with what she does with those tools: translating business questions into insights. The summary immediately names a specific accomplishment — the churn dashboard that identified 340 at-risk accounts — which proves she’s not just querying data, she’s driving decisions with it.
Every bullet goes beyond “created a dashboard” or “wrote SQL queries.” The churn dashboard didn’t just exist — it identified 340 accounts and contributed to a 12% reduction in churn. The A/B test wasn’t just “run” — it improved activation by 9% and became the new default. This is the difference between a data analyst who produces outputs and one who produces outcomes.
Listing “SQL” in your skills section tells a hiring manager nothing. Maya shows SQL depth by mentioning CTEs, window functions, and the concrete impact of optimization: cutting report generation from 45 minutes to 8 minutes. This signals she’s past the SELECT * stage and can actually write performant queries against production data.
The Tableau dashboard isn’t described as “visually appealing” or “interactive.” It’s described by what it communicated: which accounts were at risk and what the retention team should do about it. Maya also delivers monthly presentations to the VP of Customer Success. This positions her visualization skills as a communication tool, not an art project.
Instead of apologizing for not having a CS degree, Maya’s summary frames her self-taught SQL and Python as evidence of initiative. Combined with the Python automation script she built at the agency and her Tableau Public portfolio, the self-taught angle reads as “this person learns fast and builds things on their own” — which is exactly what hiring managers want to hear from junior candidates.
With only 1.5 years of work experience, Maya uses a Tableau Public portfolio to add depth. But this isn’t a generic “Projects” section — it has traction: 2,800+ views and a Viz of the Day feature. This proves she’s genuinely curious about data, not just clocking in. For junior analysts, a strong portfolio project can be worth as much as a second job.
A B.A. in Economics might feel like a weakness when competing against CS grads, but Maya turns it into a differentiator. Her summary mentions “a background in economics that keeps my analysis grounded in business context.” She understands supply and demand, marginal costs, and market dynamics — context that pure technical analysts often lack. The degree isn’t a gap to fill; it’s a lens that makes her analysis more useful.
The weak version describes a task. The strong version names the exact output, quantifies what it found, and ties it to a business result. Same dashboard, completely different signal.
The weak version is a template anyone could paste their name onto. The strong version is so specific — HubSpot, churn, 340 accounts, Q3 — that it could only belong to one person.
The weak version lists every tool ever touched plus soft skills that don’t belong. The strong version is categorized, shows specific sub-skills within each tool, and only lists what Maya has actually used to ship real work.
This exact resume template helped our founder land a remote data scientist role — beating 2,000+ other applicants, with zero connections and zero referrals. Just a great resume, tailored to the job.
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