The role of a Data Scientist is a varied one. Our Lead Data Scientist, Michael Thompson, talks about what his typical day looks like with us here at Modo25.
Mornings as a Data Scientist
I start every morning with a dog walk, regardless of the weather. This gets me up and moving and gives me a chance to think about the day ahead. Starting my day like this means that by the time I open my laptop, I’m in the right frame of mind to work.
The first thing I do is review my emails to see if there is anything important that needs adding to my to-do-list. I also make sure to or reply to as many emails as possible so that people aren’t waiting for me. Once that’s done, I’ll tend to have a look at a few blogs or LinkedIn posts to see what’s happening in our industry. Now, I am ready to work.
I work in blocks of time on a single task or problem at a time. This helps me to be less distracted and 100% focused on the task at hand. For example, if I am working on something I try not to look at emails until that task is complete. Once each task is done, I will then review any emails that have come in. No two jobs are the same and as a result, I am constantly learning new things to apply directly to what I am working on.
Data Scientist tools and responsibilities
The work I do varies a lot. Sometimes I am helping build future tech. Other times, I am helping clients or my colleagues understand the tech in the digital industry. Part of this means I use a range of tools for collecting data, storing data and processing and analysing.
- Collecting Data – I mostly use Google Tag Manager and Google Analytics. We all know that good data going in means good data coming out. We can then make better decisions and this is why this step is so important to get right.
- Storing Data & Processing and Analysing – I would use Python, R, Google BigQuery and SQL for building tech and dealing with large data sets. So much can be done here and it depends on the job in hand as to which tool/s should be used.
- Presenting Data – I would use Google Data Studio, Tableau and Excel to present my finding or create a dashboard for the end-user to understand the data. This part is what the end-user sees so it is important to get this right. This makes it easy to understand and interpret. As it is the only thing the end-users see, they do not always understand everything that is going on in the background to get to this point.
A key point in my day is lunchtime. I always make time for a break not just to eat, but I also use this time to recharge. Sometimes if I have a problem that I can’t solve, a fresh pair of eyes after lunch is all I need. I usually go for another dog walk or make lunch for me and my wife, so we can eat together.
Keeping on top of projects
There are a number of different meetings throughout the week. An important one in my diary is the client requirement meeting. This gives me a chance to make sure all data science work in on my radar and I have all of the relevant information. I have a number of catchups to develop my skills in three key areas; data, tech and business. At the same time, we go over plans for current projects and if I need any additional help with anything I can ask.
I like structure, so in order to keep on top of everything I have a Trello board. This lists everything I am working on across all clients and projects. This means I know what I am working on this week what I am waiting for feedback on. It also allows me to ensure everything is ready for next week too.
