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Resume example · Data Analyst · 5+ years

Data Analyst resume with 5+ years of experience: a sample from India

At five or more years the question is influence: which decisions your analysis changed, what they were worth and how many analysts you grew. A senior page keeps two or three programmes of work, names the stack in one line and drops the dashboard inventory.

Last reviewed
October 2026
Fictional sample
5 or more years of experience
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Summary examples for 5+ years of experience

Two ways to open the page. Neither is the summary on the sample resume beside it, so you can see more than one approach.

Summary example 1

Summary
Analytics lead with 7 years in BFSI and e-commerce. Built the experimentation programme behind 14 shipped tests worth ₹6 Cr a year and grew a team from 2 to 8 analysts. Looking for a head of analytics role at a growth-stage company.Opens with decisions and money, then team growth. Fits a lead who wants a head-of-function role.

Summary example 2

Summary
Senior data analyst with 9 years, the last 3 as an individual contributor owning pricing and demand analytics for a marketplace. Held forecast error under 5% and had 2 pricing changes adopted, worth ₹4 Cr a year. Looking for a principal analyst role without people management.Shows depth rather than headcount. Use it when you want to stay technical and avoid a management track.

Bullet rewrites, weak to strong

Each pair shows a line people really write and a stronger version of the same fact. The numbers are illustrations. If you have no number, see resume bullets with numbers when you have none.

  1. Before

    Managed a team of analysts

    After

    Grew the analytics team from 2 to 7 and gave every dashboard one owner and one reviewer; ad hoc requests to the team fell from 90 to 35 a month

    Why

    Headcount before and after, a process you introduced and a result. 'Managed a team' leaves the reader to guess size and effect.

  2. Before

    Provided insights to leadership

    After

    Recommended ending free delivery below ₹399 after a margin analysis of 1.2M orders; leadership adopted it and contribution margin rose 3.4 points in two quarters

    Why

    A decision, the data behind it and the outcome in a unit the business uses. Keep a note of how the margin gain was measured.

  3. Before

    Defined metrics for the business

    After

    Replaced 5 conflicting definitions of 'active customer' across finance, marketing and product with one, closing a 9% gap between the figures each team reported

    Why

    Metric governance is senior work. The count of definitions and the size of the gap show the problem was real and your fix mattered.

  4. Before

    Did forecasting

    After

    Forecasted quarterly revenue for 3 product lines with a seasonal model; error stayed under 5% for four quarters and replaced the guess used in budget talks

    Why

    Scope, accuracy and a period, plus the decision it replaced. State the error measure (such as MAPE) if the interviewer asks.

  5. Before

    Mentored junior analysts

    After

    Promoted 2 analysts to senior in 18 months by pairing each with a business partner and reviewing their written recommendations every month

    Why

    A count, a method and a result other people can confirm. Mentoring is believable when it names the routine that produced it.

  6. Before

    Presented to senior management

    After

    Presented a quarterly analytics review to the CEO and 5 function heads; 7 of 9 recommendations were funded and tracked in a shared log

    Why

    Audience, cadence and the share of recommendations acted on. A tracked log shows the analysis was followed through, not only presented.

Skills to list, grouped

Group skills into three or four lines and keep only those you could discuss for ten minutes. Each should appear in a bullet, a project or a certificate.

  • Analytics: Forecasting, Experimentation, Metrics Framework, Cost Analytics
  • Data stack: SQL, Python, dbt, BigQuery, Power BI
  • Leadership: Team Leadership, Stakeholder Management, Hiring

What recruiters for this role tend to look for

  • Decisions influenced, with money or time attached: a hub closed, a price changed, a launch paused, and the figure the business confirmed.
  • A metrics framework you set: how many KPIs, who owned each and what ended because of it.
  • Team scope: analysts led, hires made, how work is prioritised and who the main stakeholders are.
  • Method named briefly (forecasting, experiments, cohort analysis) with the error rate or confidence you held yourself to.
  • Stack at decision level (warehouse, modelling layer, BI tool) rather than every library. Seniority shows in what you chose to standardise.

Mistakes common at this level

  • A list of 25 dashboards built. Pick the two or three whose decisions you can name.
  • Impact numbers with no owner, such as 'saved ₹2 Cr' when finance never confirmed it. Say who agreed the figure or call it an estimate.
  • A skills block of libraries from a decade ago (NumPy, SciPy, scikit-learn, TensorFlow). Keep what the next role needs.

Section order on the sample

The sample uses the Experienced Impact template, A4 (210 by 297 mm), one column, with the sections in this order: Summary, Skills, Experience, Education. The order follows the level: experience leads, with fewer and sharper entries.

Questions people ask

Should an analytics lead keep hands-on tools on the resume?

Yes, as a single line. Hiring managers for lead roles still check that you can write the query or review the model. Keep the stack to what you chose or standardised, and let the bullets show the team and the decisions.

How do I show influence when I only recommended?

Write the recommendation and what happened: 'recommended closing 2 hubs; leadership agreed'. If the decision was not taken, say what was analysed and the value at stake. Do not claim savings the business never confirmed.

One page or two at nine years?

One page is still the safer default for this kind of resume: two or three roles, five strong bullets for the latest and a short line for earlier work. Use a second page only if every line is an outcome. The ATS-friendly resume guide covers layout.

Keep reading

Next step

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Answer a few questions, one at a time. The reviewer drafts each line, asks for the numbers it cannot guess and never adds a fact you did not give. Already have a resume? Check it first and see what a parser reads.

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