I am an experienced data journalist and editor with a strong track record of generating original news stories as well as managing and executing bigger visual projects. I started my career on Trinity Mirror's data unit (the company has now rebranded to Reach PLC) and then spent four years at the Telegraph before moving to the New Statesman Media Group to be the projects editor on a new data journalism team. After a year in that role, our team's remit was expanded to cover 20 additional titles within the portfolio of GlobalData Media, a sister company of NSMG. I was then promoted to lead the team.
I've covered a wide range of different topics - from general elections to The Great British Bake Off - and am used to collaborating with experienced journalists, designers and developers across the newsroom.
You can see my CV here for more details on the roles I've held/still hold and examples of my bylined work on my Telegraph and New Statesman author pages.
I'm adept at using Excel and Google spreadsheets, but R is my go-to analysis tool, especially for big collaborative data projects. It is a language I've been learning and working with for the past six years.
I can write scripts to scrape, clean and analyse large datasets, including geospatial data (for which I also use QGIS). I've also used R to connect to and query APIs and databases as well as for building statistical models (something I'm looking to expand upon).
Designing and building data visualisations has become a bigger and bigger part of what I do in my day job and is also something that I really enjoy researching in my spare time.
These days I have three main workflows for producing publishable data visualisations, the first of which solely involves using R. I and others on my team at the New Statesman Media Group have built our own in-house R package to achieve this and to solve the problem of creating stylish R graphics in a mobile responsive way.
The second visualisation method I employ starts with R (or QGIS in the example below) but then gets exported and tidied up in Adobe Illustrator before eventually being exported from there via ai2html. I tend to do this for more complicated charts because using Illustrator allows an extra level of control.
The third, and final, way I make data visualisations is with the d3 JavaScript library, which is fantastic for interactive and/or regularly updated charts. I've built visualisations such as this for use in big news events such as general elections as well as for projects that rely heavily on user input.
My JavaScript skills extend beyond d3 to more general front-end web dev areas. This can be seen in my work building things like postcode lookup tools and news games/calculators as well as this website you're reading now. You can see an example d3 visualisation by me below (and here on GitHub).
I'm always looking for ways I can expand upon my web development skills. The next thing on my list is a modular component based library like React or Svelte.
I've taught data analysis and visualisation in various settings, from formal data journalism teaching as a visiting lecturer at City University London to more informal in-house training sessions with journalists.
I'm always open to new teaching opportunites, so get in touch if you think my experience might be useful to you.
