"Financial analyst" covers work that has little in common day to day. An FP&A analyst at a software company runs the forecast cycle and partners with department heads on budgets. A corporate development analyst builds acquisition models. An equity research associate writes notes on a coverage universe. A credit analyst sizes counterparty risk. The title is the same and the screening criteria are not.
The first job of the CV is therefore to say which of these you are, quickly. The second is to show judgment rather than tool proficiency, which is where most of these CVs fall down.
The recurring fault: modelling as the achievement
A great many analyst CVs read as a list of artefacts. "Built three-statement models." "Prepared monthly variance analysis." "Developed dashboards in Power BI." Every one of these describes work that was produced, and none says whether anyone did anything differently as a result.
Financial analysis is a decision-support function. Its value is realised when a decision changes. A CV that never connects analysis to a decision is describing the mechanics of the job while omitting the point of it.
Weak: "Prepared monthly variance analysis for departmental budgets."
Better: "Ran monthly variance analysis across eleven cost centres; traced a recurring overspend to duplicated vendor contracts across two regions, and the consolidation that followed removed roughly £340k of annualised cost."
Weak: "Built three-statement financial models for potential acquisitions."
Better: "Built the operating model for six acquisition targets in the £20–80m range; the sensitivity work on customer concentration for one target reframed the committee discussion and the deal was not pursued."
That second example is worth noting: the deal did not happen, and it is still the stronger bullet. Analysis that prevents a bad decision is exactly as valuable as analysis that enables a good one, and saying so demonstrates that you understand what the role is for.
Scale and scope belong on the page
An analyst who forecasts a £4m departmental budget and one who owns a £400m P&L are doing recognisably different jobs. Reviewers cannot tell which you are unless you say. Include, where relevant:
- Revenue or budget under your analysis
- Number of cost centres, business units, entities or legal entities
- Deal sizes and count
- Portfolio or book size
- Reporting audience: whether your work went to a manager, a CFO, an investment committee or a board
- Team context: whether you were one of twenty analysts or the whole finance function
That last one matters more than people expect. Being the only analyst at a fast-growing company is a different and often more impressive job than a junior seat in a large team, and the CV should make it visible.
Say which specialism you are
Put it in the summary line. "FP&A analyst, four years, SaaS: owns the annual planning cycle and monthly forecast for a £60m ARR business" is placeable in one read. So is "Corporate development analyst, three years: mid-market industrials M&A, twelve completed transactions."
Vagueness here is costly, because a reviewer with a specific opening will simply move on rather than work out whether you fit.
Keywords, by specialism
Recruiters search their databases by keyword, so name the specifics.
FP&A: budgeting, forecasting, variance analysis, rolling forecast, month-end close, management reporting, KPI reporting, business partnering, headcount planning, scenario modelling, and the actual systems: NetSuite, SAP, Oracle, Workday Adaptive, Anaplan, Hyperion.
Corporate finance and M&A: three-statement modelling, DCF, LBO, comparable company analysis, precedent transactions, accretion/dilution, due diligence, valuation, CIM, data room.
Investment and research: equity research, financial statement analysis, sector coverage, earnings models, initiation notes, portfolio analysis, risk metrics.
Across all of them: Excel at the level you actually work. Name specific capabilities such as Power Query or advanced modelling rather than "advanced Excel", which everyone claims. SQL if you have it, and it increasingly matters. Power BI or Tableau. Python or R for the analytics-heavy roles. Accounting standards where relevant: IFRS, GAAP.
Qualifications are load-bearing in this field in a way they are not in some others. CFA level and status, ACA, ACCA, CIMA, CPA, or an in-progress qualification with the expected completion date. Put them in the header area, not buried at the bottom.
Accuracy is being assessed by the document itself
This is specific to finance. The CV of a person whose job is precision is read as a work sample of precision. A number that does not add up, an inconsistent date format, a currency symbol used carelessly, or a typo in a figure does disproportionate damage here compared with other professions.
Be consistent about currency and units throughout, use the same date format everywhere, and check every figure you cite. Have someone else read it. You will not catch your own transposed digits.
Confidentiality
Deal and client information is frequently confidential. The convention is to describe rather than name: "a mid-market industrials manufacturer, c. £45m revenue" rather than the company. Reviewers understand this completely, and a CV that names things it should not raises a genuine question about judgment.
Format
One page for under about ten years, two beyond. Single column, standard headings, contact details in the body rather than a document header, real text rather than images. Investment banking and some investment management screens have their own strong formatting conventions, so if you are targeting those specifically, follow the format your target firms expect.
Check the parse with the free ATS checker, which shows the extracted fields as well as a score.
