Portrait of author Amy McQueen
Amy McQueen

Data Science Graduate

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Why I joined Peak as a Data Science Graduate

By Amy McQueen on December 10, 2021 - 10 Minute Read

Hello! I’m Amy, I joined Peak as a Graduate Data Scientist in September. There are eight of us in the Peak graduate data science scheme, we’re the first cohort to join but we won’t be the last! We’ve agreed to write a series of blogs – a diary, if you will – of our experience during our first year at Peak.

I’m up first, so I’d like to share with you how I found out about Peak, why I chose to apply, and what my experience has been like as a Data Scientist on Peak’s brand new graduate programme.

Finding out about Peak

I joined Peak immediately after finishing my Medical Sciences degree, so I’d spent quite a lot of time during my final year thinking about jobs, careers, sectors and what kind of work culture I’d be best suited to. As part of my undergrad, I did a year in industry working as a data analyst, which I really enjoyed, so I was excited to get back out into the workplace. During my year as an analyst, I had taught myself how to code in R and loved it. It opened my eyes to data science, the challenging problems a data scientist looks to address in their day-to-day, and I knew then that a career in data science would really excite me.

So I started by searching the internet for ‘the best places to work in tech’ and ‘best data science companies’. That’s how I found Peak. They had just been awarded a best companies award, ranked the 10th best company to work for in the technology sector. I started looking at their website and reading their blog posts. Congratulations reader, you have already found this blog and saved yourself a lot of time compared to me!

So, what stood out to me about Peak?

There were five reasons that Peak stood out to me initially and, after two months working here, they remain true. So, here’s the top five reasons why Peak seemed like a really good place for me:

  • Everyone at Peak is really smart. I knew that if I could be around super smart, innovative people every day, I would learn so much and always feel driven to learn that extra bit, challenge myself in that extra way and basically never get bored. When looking around at my options, I couldn’t find a team which worked on a more diverse and wide-ranging repertoire of data science problems.
  • Peak cares about its people. All the cool pictures of the office, the instagram account full of socials and cool merch – it all gave me good vibes. But also the Peak values seemed really well thought out and instilled throughout the company. The little things add up too: discounts/memberships for gyms, mental health apps, therapy sessions.
  • Peak has a growth mindset. Joining a company of Peak’s size and with Peak’s levels of ambition and investment is a really exciting opportunity for a graduate. I was thinking to myself, where could Peak be in two or five years’ time? Where could I be? Well, geographically with Peak, I could be in Manchester, Mumbai or New York City – and who knows where else? Each employee gets a lot more opportunity to shape best practices and ways of working within the company, to help the company grow in the best way possible.
  • Peak has a flat hierarchy. I liked the idea of working in a relatively flat hierarchy, it means a lot of people get a lot more work done and everyone in the team is empowered to take responsibility for their own projects and day-to-day work.
  • Peak is based in the North! Wow, this was refreshing. A cool, tech scaleup which wasn’t based in Central London? Would my salary at Peak actually cover my rent, bills AND a beer? Manchester is a great city, it’s similar to Leeds where I was at university, so I knew I’d like it here.

Each employee gets a lot more opportunity to shape best practices and ways of working within the company, to help the company grow in the best way possible.

Applying to Peak

With all this in mind, Peak seemed a great place to work and when I saw the graduate scheme job advert, I got straight on it. The application process was really smooth and a nice balance of technical and non-technical questions. I was given a data science task to complete which involved analysing a dataset, building a model and making recommendations off the back of my findings. I enjoyed the data science task and when questioned about it at the assessment day, I wasn’t made to feel inexperienced or out of my depth. The Q&A session was also a really good way of asking the data scientists questions about their work and what Peak was like.

I found Peak’s values came across to me throughout the recruitment process, and are central to all of Peak’s actions day-to-day. Meeting people at Peak gave me huge confidence in my decision to apply here and that joining this team would be all I had hoped it would be.

Fancy joining Amy and our other Data Science graduates?

Find out more about our Data Science Graduate Scheme.

First few weeks at Peak

Starting at Peak in September 2021 was great timing. The UK was starting to get back to the office after the Covid-19 pandemic and Peak were joining suit with a flexible working arrangement. It was really nice to be able to meet people in person and be in Peak’s awesome office (we call it a Clubhouse, it’s less formal than an office and includes different spaces for different types of work) as well as working from home. Also, Peak was just about to host their inaugural decision intelligence summit – Altitude X – so that was creating a real buzz around the office!

The first week was spent with the other seven new graduates, getting to know each other and what to expect on the graduate scheme. This was a really nice, gentle introduction and gave us a lot of time to get familiar with how the year’s scheme is likely to pan out. 

The other graduates and I then started two weeks’ of company-wide onboarding, where we met some other new Peakers from across the company and were introduced to every team, what they do and who they are. This was absolutely brilliant for learning about the Decision Intelligence category, the sales, marketing, executive board, business partnerships and engineering sides to Peak which I might not come across every day as a data scientist. 

By being in the office and meeting people, you could tell that there’s a focus from the People team on recruiting great people that embodied Peak’s values. Everyone was so approachable and friendly that when I inevitably broke a few lines of code (or my entire Git account), I wasn’t too scared to go and ask for help from colleagues.

First two months at Peak

In my fourth week at Peak, I started to get properly stuck in. I had read up on the customer solution I would be helping on for the next three months and I’d started being assigned tasks to help the lead data scientist on the project. 

We are helping a business understand their customer base better and where to focus their marketing and sales efforts. Answering questions like, which customer group are in-market? Which are expected to churn? Who are the most valuable long-term customers

Alongside this, we have built a recommender for their website. When an online customer puts an item in their basket, they are recommended similar products which are commonly bought together. We are now just launching a pricing optimisation project, too. This is a brilliant project for me, I am working on a number of different data science solutions at different stages of development.

There’s too many other exciting things going on for us grads at Peak to go into too much detail, but here’s a taster: 

  • Graduate initiative time: group data science project separate to our customer work, completely scoped out and developed by the grads. 
  • Graduate and Peak academy sessions: weekly skills sessions about all sorts of technical, non-technical skills.
  • Weekly Friday beers, 5-a-side football, running club and board games night!


Every work day challenges and engages me, and I’m pleased to be a part of Peak. I can’t wait to see where I am in a years’ time. If you’re interested in joining Peak, check out our Spring 2022 Graduate Scheme.

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