Data Analyst Resume Sample for Indian Freshers (2026)

A real ATS-friendly resume sample for Data Analyst (Fresher) (0-1 years, Data / Analytics).

Sample resume

Priya Iyer — Hyderabad, India

Data analyst (B.Sc Statistics + GTM analytics certificate, 2025). Built 2 production dashboards used by 40+ internal users at a Bangalore D2C startup during internship. Strong on SQL, Python pandas, Tableau, and statistical analysis. Looking for a Data Analyst role at a product company where I can own metrics + insights end-to-end.

Experience

Data Analyst Intern — Kapiva Ayurveda (Bangalore, hybrid) (Jan 2025 – Jun 2025)

  • Built repeat-purchase cohort dashboard in Tableau (data: Shopify + GA4 via BigQuery); identified 3 product categories with 2x higher retention, drove ₹12L additional repeat revenue in Q2.
  • Wrote 30+ SQL queries to power weekly business review (BigQuery + Looker); cut analyst response time on ad-hoc requests from 2 days to 4 hours.
  • Ran A/B test analysis on checkout funnel changes (Optimizely + Python pandas); identified that simplified address form lifted conversion by 4.1% (p < 0.05).

Education

B.Sc, Statistics (Honors), St. Xavier's College, Mumbai (2022 – 2025) — CGPA: 8.9 / 10.0 · Coursework: Probability, Inference, Regression, Time Series, ML Foundations

Skills

  • Languages: SQL, Python, R
  • BI / Viz: Tableau, Looker, Power BI, Excel (advanced)
  • Data Stack: BigQuery, PostgreSQL, dbt (basics), Google Sheets
  • Statistics: Hypothesis testing, A/B testing, Regression, Cohort analysis

Projects

India Air Quality Dashboard (Tableau Public)

  • Public Tableau dashboard analysing 5 years of CPCB air-quality data across 30 Indian cities; 1.2K+ views in 3 months.
  • Built ETL pipeline in Python to clean + enrich raw CPCB CSVs (handling missing data, station consolidation, seasonality adjustments).
  • Wrote a 1,500-word blog post explaining methodology + key findings; reposted in r/IndiaSpeaks (180+ upvotes).

Cricket IPL Match-Outcome Predictor

  • Logistic regression model in Python (scikit-learn) predicting IPL match outcomes from historical data; 67% accuracy on held-out 2024 season.
  • Feature engineering: team form, head-to-head record, venue-specific win rate, toss outcome.
  • Open-sourced on GitHub with reproducible Jupyter notebook + requirements.txt; got 22 stars in first month.

Why this resume works for ATS

  • Numbers in every bullet — recruiters scan for "₹12L revenue," "67% accuracy," "1.2K views" before reading any prose. Generic analyst resumes lose to ones with quantified impact.
  • Tools section groups logically (Languages, BI, Data Stack, Statistics) instead of one wall of buzzwords. Recruiters can quickly check stack-fit.
  • Projects show real-world data work, not toy datasets. CPCB air-quality and IPL data are India-specific — signals you understand the local data ecosystem.
  • Summary positions for product-company analyst roles specifically (not consulting, not enterprise BI). Narrow targeting beats trying to be everything.
  • Statistics coursework is called out — for analyst roles, recruiters often filter on stats background. Don't hide it under generic "B.Sc."

Common mistakes for Data Analyst (Fresher) resumes

  • Listing 15 BI tools (Tableau, Power BI, Looker, Metabase, Mode, Superset, Sisense...). Pick 3-4 you can demo. Tool sprawl signals shallowness.
  • No projects, only coursework. Coursework alone doesn't differentiate — every B.Sc Stats grad has done regression in a class. Public Tableau + GitHub + a real-world dataset is the bar.
  • Vague bullets like "analysed customer data." What data? What did you find? What changed because of it? Specificity wins.
  • Forgetting domain context. "Built dashboard" is weak. "Built repeat-purchase dashboard for D2C team that drove ₹12L revenue" is strong — domain + impact.
  • Including all certifications. One Google Analytics cert is fine; 8 Coursera certificates dilutes the signal. Pick 2-3 most credible.

Frequently asked

Do data analyst roles really require coding?

Yes — at every product company. SQL is non-negotiable; Python or R is required for at least 60% of analyst roles. Pure-Excel analyst roles still exist at services companies and traditional enterprises but are declining. Plan to know SQL well + Python pandas at minimum.

Is Tableau or Power BI better to learn?

Tableau dominates Indian product startups (Swiggy, Razorpay, CRED use it). Power BI dominates enterprise / Microsoft-stack companies (Infosys, Wipro internal, banks). Learn one well rather than both badly. Tableau has free public tier — easier to build a portfolio.

How much SQL do I need to know for a data analyst interview?

For freshers: SELECT, JOINs (inner, left, right), WHERE/GROUP BY/HAVING, window functions (ROW_NUMBER, RANK, LAG), CTEs. Most interview SQL questions test window functions specifically — practice 20-30 problems on LeetCode SQL or DataLemur.

Should I get an MBA before going into analytics?

Generally no — for IC analyst roles, an MBA isn't required and may overqualify you for entry-level. MBA + analytics makes sense if you're targeting analytics-consulting (McKinsey QuantumBlack, BCG Gamma) or analytics-management roles. For data analyst at a product company, a B.Sc/B.Tech + portfolio is faster to job.