Data journalism is the part of the newsroom that answers questions with evidence instead of adjectives — and it is the discipline this publication runs on. The path in is more open than it looks: newsrooms increasingly hire for demonstrated method rather than credentials, and the tools are free. Here is what the craft actually involves and how to build toward it.
What the job is
Day to day: a story breaks, and the data journalist finds the dataset that sizes it; a claim circulates, and they verify or correct it from the original source; an investigation needs a database built from a thousand PDFs, or a Freedom-of-Information request drafted so the records actually arrive. The output ranges from a single number in a sentence to a full analysis with charts and a documented method. The constant is that every figure can be traced, and the reader can check it.
The skills, in order of acquisition
1. Spreadsheets, properly. Pivot tables, lookups, basic statistics, and the discipline of never editing the raw sheet. Most breaking-data work happens here, and fluency shows.
2. Finding data. The primary-sources method and the economic-data map cover this: statistics agencies, filings registries, court records, FOI requests. Knowing where data lives is a hiring differentiator because it cannot be faked in an interview.
3. SQL. Most interesting data arrives as a database, not a spreadsheet. SQL is the language of asking it questions, and it takes a fortnight to become useful.
4. Python or R. For analysis beyond spreadsheet scale: cleaning messy files, joining datasets, statistical tests, reproducible scripts. Python's pandas is the newsroom standard; R's tidyverse is its peer. Either is fine; depth beats breadth.
5. Charts that tell the truth. Not decoration — encoding. Knowing when a line chart misleads, why dual axes are usually a lie, how to show uncertainty. Study the graphics desks of the FT, the Economist and the BBC as a reader first, an imitator second.
6. Reporting. The non-negotiable. Data finds the pattern; sources explain it. Interviewing, attribution and verification are the journalist half of the title, and analysts who cannot report remain analysts.
Building a portfolio from nothing
The loop that works: take a dataset that already exists publicly, related to a live story; analyse it honestly, including the parts that complicate your finding; publish the result anywhere that will hold it — a personal site, Medium, a newsletter — with your method shown: data used, steps taken, code or queries included. Repeat.
What editors look for in such pieces: a question a reader cares about; sourcing for the data; correct handling of definitions and revisions; charts that survive scrutiny; and plain-language explanation. What they do not need: another restatement of existing coverage.
Three strong pieces is a portfolio. Twenty links to reposts of other people's analysis is not.
Getting in
Trainee schemes and fellowships. The BBC, Guardian, FT and regional groups run structured schemes annually; data-adjacent applicants with portfolios regularly place through them. IRE and NICAR in the United States run training and job listings specifically for this craft.
Adjacent doors. Research roles at think tanks, NGOs, transparency organisations and universities use the same skills and pay during the transition; many data journalists arrive via that route.
The direct route. Pitch a data story to an editor: one paragraph, the finding, the dataset it rests on, why now. Editors say yes to evidence, not to interest. A small published piece leads to the next one.
Where the field is going. AI has automated chart-making and raised the value of what cannot be automated: knowing which question matters, which dataset is trustworthy, and which finding is an artefact of the cleaning. The verification skills in our fact-checking guide are the part of the craft that appreciates.
One more route
We are building The Meridian Report's contributor bench with people who work exactly this way — research from primary sources, every figure traceable, analysis in plain language. If you have portfolio pieces in that spirit, we would like to see them.