I'm looking to transition from academia to data analysis. My core strengths are strong quantitative skills, with a history of analysing and summarising specialist data (MRI data; time series analysis, similarity analysis, statistical summaries etc.). These skills transfer easily to other domains. I have over a decade of programming experience (starting with Turbo Pascal (!), but now predominantly Python and R). I'm a fan of vim, but I've not yet managed to use regular expressions without a cheat sheet or two!I enjoy the challenge of communicating analysis to lay audiences, and whilst I love teasing patterns out of data, it's important to me that I get the opportunity to interpret and present the results too. I want the story the data tells, not just the numbers.I'm particularly interested in data analysis as a career, as it's a fast moving field. Whilst classic linear analyses are not to be underestimated, techniques are developing rapidly as computing power grows, so there will always be the opportunity to learn. It was partly what drove me to cognitive neuroscience; the field is barely as old as I am, so even during my PhD I saw analytical approaches adapt and evolve. A single paper might open up whole new avenues of research. That is what I'm hoping for, in my future endeavours.