What does this even mean and why are people putting it on their CVs? 🙂
Towards the end of 2020 I was lucky enough to be hiring for several new positions in my team1. Given the times that we are in, there are many more applicants for roles than there was even a year ago. I’ve spoken before about the skills that you need to get a role as a data scientist and there are specific things I expect to see so I can judge experience and competency when I’m looking at these pieces of paper so I can decide who I want to interview.
Sadly I’m seeing a lot of cringeworthy things on CVs that are the fastest way to put a candidate on the no pile when they reach me. These things might get you past HR and also past some recruitment agents, and I wonder if this is why candidates do them. I try and give as much feedback as I can, although sometimes the sheer volume of CVs and the time taken for constructive feedback would be more than a full time job. By sharing some of these things more publicly I hope to pass this advice on to as many as possible.
We’re just over a week into 2021 and I’ve been back at work (from home) for five days after a lovely two week, very relaxing break. The lockdown order was probably the best thing for me mentally as it completely removed all of the normal pressures of the Holidays. There were no long drives to family and finding someone to look after the cats while we were away, no rushing to fit in the trips to Santa or pantomimes. no panicking that we needed things in just in case we had visitors, and no injuries this year1. It was two weeks of pure, uninterrupted relaxation. I do miss my friends and family, but I am one of those people who just doesn’t stop and the only way I do is when I literally can’t do anything else.
October has always been a super busy month for me. I’m usually starting a new OU module and travelling around speaking at conferences and meetups, all while doing my day job, spending time with my family and enjoying my hobbies. Sometimes I’ve not got the balance right! 2019 I remember was particularly hectic. I optimistically submitted conference sessions at the start of the year on a variety of different topics and, as the year went on I was invited to speak at various meetups in the UK and even stepped in to do some last minute presentations where other speakers had dropped out. This time last year I had just finished 8 weeks where I had a week’s holiday, spoken at 5 conferences, 2 breakfast briefings and 8 meet ups, all of which were on slightly different topics!
It’s been seven years of studying while working full time (and in some cases nearly double full time hours!) and I’ve now finished the degree I started for “fun” because I wasn’t being intellectually challenged in the job I had at that time. I was sceptical of all aspects of the Open University but thought I’d give it a go, knowing that without a cost to me and an exam, I would never make the time to study. While I’ve been blogging about individual modules over the years I’ve had quite a few conversations with many of you reading this blog about the pros and cons of study with the OU and one of the comments on my last post was from Korgan, who suggested I do a post about this and I’ve combined their questions with all of the others I’ve had.
There are a lot of people interested in data right now and there are a lot of visualisations to make that data easier to consume for people who are not data scientists. However, like any branch of statistics, visualisations can easily mislead. We are programmed to see patterns. If we are presented with a graphic that supports the surrounding text then we are more likely to believe the argument presented without further research1. I wrote about this on the Royal Statistical Society Data Science Section Blog in May, where reversing the colours in successive graphics can cause confusion. I’ve seen further examples and one caught my eye this month because it was being called out.
Seven years ago I was in work bored and desperate for a new challenge. My daughter had recently been born and I had decided to stop playing World of Warcraft. Needing a new challenge, I had toyed with an MBA but really wanted to do something for me. So I signed up for a BSc in Mathematics with the Open University, which I knew would take about 6 years part time while working. This week, I got the results for my final module and it was confirmed I had earned a first class honours degree. But why didn’t I do maths the first time round?
It’s been possible to run Linux on Windows for a few years now. Windows Subsystem for Linux (WSL) was released in 2016, allowing native Linux applications to be run from within Windows without the need for dual boot or virtual machine. In 2019 WSL2 was released, providing a better architecture in terms of the kernel and improving the native support. A few weeks ago, Microsoft and NVIDIA announced GPU support on WSL2 and the potential for CUDA accelerated ML on Ubuntu from within Windows. Before I dive into this in detail, I want to take a quick aside into why you might want or need to do this…
While it’s no secret I love Lego and tech in general, I also love the educational STEM toys that are released. Sometimes, the ages on the toys don’t always make sense for their complexity, leaving a child who is either frustrated at something too tricky or too simplistic. Both can leave a young person slightly disengaged with STEM, the exact opposite of the idea of these toys!
Christmas 2019 I was given this Hydraulic Robot Arm kit, suitable for ages 10+1. With work, OU study and general life I’ve only just got around to building it2. So, let’s take a look – is it suitable for ages 10 and up for both build and principles it teaches?
This week I was due to be sat in a large hall with about 200 other Open University students taking my exam for module M347, the last of the modules for the BSc in Mathematics I started for “fun“1. As with students in traditional universities, March 2020 gave a lot of uncertainty2. While some modules were switched to be coursework based assessment, mine was confirmed to be a remote exam with the originally planned exam paper. The paper would be accessible as a PDF on the day of the exam and then submitted in two parts: a multiple choice computer marked section and then a human marked second section. We would not be time limited (other than by the 24 hours in the day!) So how did I feel about this and how did it go?
There’s a trend in job descriptions that the company may be looking for “Data Science Unicorns”, “Python Ninjas”, “Rockstar developers”, or more recently the dreaded “10x developer”. When companies ask this, it either means that they’re not sure what they need but they want someone who can do the work of a team or that they are deliberately targeting people who describe themselves in this way. A couple of years ago this got silly with “Rockstar” to the point that many less reputable recruitment agencies were over using the term, inspiring this tweet:
Many of us in the community saw this and smiled. One man went further. Dylan Beattie created Rockstar and it has a community of enthusiasts who are supporting the language with interpreters and transpilers.
While on lockdown I’ve been watching a lot of recordings from conferences earlier in the year that I didn’t have time to attend. One of these was NDC London, where Dylan was giving the closing session on the Art of Code. It’s well worth an hour of your time and he introduces Rockstar through the ubiquitous FizzBuzz coding challenge.
After watching this I asked the question to myself, could I write a (simple) neuron based machine learning application in Rockstar and call myself a “Rockstar Neural Network” developer?
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