After a quick walk from Liverpool Street station, I arrive at our building on Clifton Street. For the first 15 minutes of the day, I go through my emails and fill up my daily planner with tasks I need to complete for the day. Afterwards, I have a weekly catch-up with my manager where we discuss my progress and work from the previous week, as well as my tasks, aims and goals for the upcoming week. I also ask any industry or company questions to help me better understand my role and contributions to the team.

After our meeting, I begin my first task of the day. I started as a graduate analyst in December 2022 and my role in the company is a unique hybrid between analyst and tech team member (Futures has a small technology team that are responsible for maintaining and developing our technology stack, as well as building custom tools/dashboards to make the lives of our analysts easier and to improve access for our clients). With a proposal deadline coming up, I am assigned to help with the creation of our interactive dashboards. My fellow graduate analyst and I are allocated the job of creating configuration files to ensure that the data is uploaded efficiently and consistently.

I have a meeting with members of a different client team on their social media data collection. One of my main roles in the company is to handle and investigate the multimedia processes of scraping and collecting social media posts relevant to our clients. The data is then used to calculate the value generated from exposure of sponsor logos or tags within these posts. In this particular meeting we discuss how to improve data quality and collection, to ensure datasets are full and comprehensive.

This is an example of a new skill I’ve had to learn on the job. As someone with aspirations to grow my career in data science and engineering, I’m always excited to take on these data challenges. The company also provides many other opportunities for me to do so. For instance, one of my earliest and most important projects has been using machine learning and regression algorithms to assess social media impressions for our clients’ posts across various platforms.

The team and I head out for lunch. Most of the team likes to head to the nearest food market right outside the office then head back to eat and socialise. Since we are a relatively small team, it makes everyone feel closely knit, with all levels of the team mixing. After eating we even enjoy some fun, yet competitive, games of table tennis to see who reigns supreme within the team.

Weekly team meeting time. This meeting is hosted by a different graduate each week, and in it we go through the latest company and account updates. All members of the team are given the opportunity to share updates on their accounts, do a demonstration of some recent work or talk about industry trends/recent events they’ve been able to attend. We end the meeting with something fun, decided by that weeks host. This week we’ve got a short quiz on the week’s key sports news, but we’ve also had blind taste tests and highlights from another graduates boxing fights, amongst other things!

I have been working on my research project for about a month now. It is gradually coming together, and I am fortunate to be working with a more senior colleague (my buddy when first entering the company) who is happy to teach me new things. We are working on a new Python script to scrape Instagram posts and I learnt how to use the Spyder IDE. It would have been quicker for my colleague to program the script himself, but he has instead chosen to teach me as we go along. This has been a fantastic learning experience, and I’m grateful for his help. This reflects how everyone at Futures is always eager to help and lend assistance, creating a great environment to work in.

Time to do some social media post data checks. Overseeing the social media multimedia processes means that I monitor the volume and quality of social media data we’re collecting. I open my script of splash page queries to run and analyse the number of posts we are pulling in. I also assess the queries used to collect and scrape the data and check all posts are relevant. I raise any issues with the tech team and brainstorm ideas on how to resolve and prevent these errors in the future.

I pack up my things and make my way home after an eventful yet rewarding day of work.