Data science graduate diary: Ready, set, go!

Get ready: Applying to Peak

I came across Peak last year during my Master’s degree at the University of Manchester. It was through one of my professors who was giving a speech along with a data scientist from Peak about resource-constrained optimization and nature-inspired algorithms at one of Peak’s Ensemble events. Sounds cool, right? Well, it was.

So, a couple of months later when I saw the announcement about the grad scheme I didn’t waste my chance and applied. The coding exercise we had to complete and the assessment day may sound intimidating but they turned out to be a really fun experience and I was quite excited to meet so many people from Peak. And then, Lorenzo – our Head of Talent – called me, and I was in!

Set: Get onboard!

If I had to choose a word to sum up my first month at Peak, that would be ‘information.’ The first month here was all about us gaining information about every aspect of the company through a range of onboarding sessions. We learned how the department of data science operates, as well as every other team – from product right through to finance!

Gaining a general overview of the whole company and actually seeing how everything comes together helped me immerse myself pretty quickly in this new environment. Another really important aspect for me was to be in a place where I would feel comfortable to ask questions without hesitance, learn and develop constantly.

So, I was more than glad when I realized that Peak’s culture really reflects on its people. Everyone is very approachable and always willing to give me some help and spot-on answers to my questions. I was more than pleased to see that the drive is high and every day there is something new to learn and a new skill to develop.

Go: My first Insight-ful rotation!

The graduate scheme consists of four rotations across different DS teams: Insights, Operations Retail, Operations Manufacturing and Research and Development. My first rotation was at Insights along with my fellow graduate, Daniel. 

Generally, in Insights, data scientists use analysis and visualizations to spot patterns in data and provide recommendations to improve the decision making of our customers. During our onboarding at Insights, we were given presentations on topics like how to scope an insights project and how to build an insights deck. 

After the first couple of weeks of onboarding and developing some basic insight skills, Daniel and I started working on our project. The primary focus of the work was producing an insights report for FareShare Greater Manchester. For those who don’t already know, FareShare’s Greater Manchester (FSGM) mission is to redistribute surplus food to charities and community members in need and reduce food wastage. To do that, FareShare relies on food donors that provide them with their surplus food. If you are interested in learning more about FareShare’s mission and how AI can be used for a positive impact you can take a look at this article by my colleague Oskar, one of the many amazing data scientists at Peak.

Daniel and I were helping to create impact reports for FSGM’s donors. Our aim was to provide them with an overview of their donations and how these had an impact on people in need. To do that, we had to deploy our skills in R, and guess what? Neither of us had used R before! With the support and guidance of the Insights team, we learned how to create an impact report using R and RMarkdown, so that one report could be created for each individual donor. 

To step up our game and automate the process of report generation, we decided to create a WebApp using RShiny where the users can generate the impact report they need by using filters like the donor they want, specific timeframes, etc. One of the parts I enjoyed the most during my rotation – apart from learning how to actually handle the data to produce insights and seeing how insights can impact decision making – was mastering RShiny. Basically, RShiny is now my new best friend!

Alongside our rotations, we’re all getting involved in a graduate project as well. Three of my fellow grads and I are currently working on a forecasting solution for FSGM. This was something very new to me; it was the first time I was collaborating with other people to solve a complex problem from the beginning of the ingestion of the data to the end of delivering a solution outcome. It was also a great opportunity to learn more about forecasting and how it can be applied to a real-life problem. So far, I have learned a lot by collaborating with these brilliant grads and from the amazing data scientists that are helping us.

Post-credits: AltitudeX, sports and Werewolf.

Of course, the highlights of my first four months at Peak don’t end here! In November, Peak launched AltitudeX, our first AI and Decision Intelligence Summit. We welcomed 700 people to Depot Mayfield in Manchester. The day was filled with very interesting talks regarding topics around data and decision making from remarkable speakers like Leanne Kim Fitzpatrick, Head of Data Science at The Financial Times, and Christopher Wylie, the Cambridge Analytica whistleblower. I particularly enjoyed the technical workshops,  since they presented more practical topics and data science solutions talks. A detailed review of AltitudeX can be found in Jon’s blog post, here, for anyone interested.

Lastly, another very important aspect here at Peak is our wellbeing. My favorite parts of that are the company activities and the wellbeing meetings. Recently, I joined the 5-a-side football games that take place every week. Not only do I enjoy playing football, but I also get to spend time with my work mates outside of work. The wellbeing meetings are also a nice chance to socialize with people from work and have a quick break during the day. During these we normally play a quick game like Werewolf, which I have to admit that I am obsessed with. 

I tried to quickly summarize my first four months’ experience on the grad scheme here at Peak, but there is so much I couldn’t fit in! If you liked what you read and want to be a part of our team, you can apply via the button below – we are currently accepting applications for the new awesome team of grads in September 2022. We’re looking forward to hearing from you!