Data Science progression at Marshmallow

A happy Marshmallow Data Scientist

Data science at Marshmallow

Officially, the Marshmallow Data Science team was born on 10th June 2019 — with their first appointment of a dedicated data scientist 💼. But a data-driven approach had always been at the forefront of the co-founders’ vision. Harnessing the power of data is the future 🔮, and it’s the best way to disrupt an industry as antiquated as insurance — because up ’til now — insurers haven’t been making effective use of the huge amount of data at their fingertips. Intelligent use of data, and investment in analytics, has equipped us with the means to innovate — giving us a significant advantage over our competitors. This means that, since early June ’19 we’ve gone from one to six data science team members — with the view to continue that growth 📈. But it’s not just about quantity…the quality of the people in our team is what’s allowed this corner of the company to make such an impact. Marshmallow’s got high recruitment standards, and as we look to grow, we want to make sure we’re conveying the opportunities that strong candidates could have here — in order to reel in the best talent.

We’re looking for talent

Recruitment in start-ups is notoriously challenging. To attract and retain the best talent we need to communicate how we work, why it’s superior, and what our values are. Transparency here will only serve to engage the candidates who are up to it. As well as limiting any concerns they might have about jumping into a company that’s relatively new 🐣. With data proving to be the most powerful commodity for the future of big business, the market for top grade data scientists is pretty competitive 🥊. We need to make our positions appealing to ensure the best candidates don’t get snapped up elsewhere. The second challenge is holding onto them. Our roles demand driven, high-functioning individuals who seek stimulation from their jobs. That means it’s our job to retain that interest and make sure they continue to feel fulfilled and challenged in their work. So how do we do that?

A career progression framework

At Marshmallow we have five core values: we move fast, we are selfless, we take ownership, we are open and honest and we pioneer. These principles permeate the way we work together day-to-day and provide a unique work culture that balances easy communication 📣 with rapid progress ⏩. These aren’t just abstract ideas though — we’re always reflecting on them and we put tangible processes in place to make sure they’re upheld.

We’ve created a new Data Science career progression framework with this in mind.

The idea of the framework is to outline the expectations and skills of a data scientist across five main groups: communication, delivery, team member, technical skill and long-term strategy — emphasising the company’s values within each skill. The positions range from a Data Analyst to Lead Data Scientist. We think this transparency will appeal to the self-aware, ambitious people that we want to attract to the team 🧲. The draw of older businesses can be the clear career-ladder they offer, but this framework does more than specify rungs — instead it builds a full picture of a what a role entails and the skills that can be developed and put to use there

Autonomy at Marshmallow

We want to build autonomous teams at Marshmallow, channeling the leader-leader philosophy, instead of the leader-follower. No one person dictates what is and isn’t done — we all get to enjoy the freedom and challenges of individual accountability. We’re open about sharing our failures and learn from them as a team 🙌. We give credit to our unique culture for the huge growth and success Marshmallow’s seen over the last year — and we hope that frameworks like this will help convey that to the prospective candidates we’re looking for.




We are Marshmallow — a fintech on a mission to make insurance cheaper, faster and fairer for everyone by using tech to our customers’ advantage.

Recommended from Medium

How Exploratory data analysis can help you understand users

Revisiting China amid the coronavirus pandemic

This Data Science Discovery is Shocking!

Fit for Data Science

House Prices Prediction: An implementation of advance regression techniques to predict Housing…

Automated Visualization with AutoViz

Data Experts Weigh-in On The Future Of Data

Analytical study of climatic conditions of Shannon Airport

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
Paul Elliott

Paul Elliott

Lead Data Scientist at Marshmallow

More from Medium

Switching roles from Business to Data

AI/ML in B2B Enterprise Life Cycle Optimization

What is SKAdNetwork?

Net-Zero is where we need Exponential Growth