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Data

Image of the title that reads: 'How we use incremental modelling to handle billions of events every day' in hot coral writing, with a turquoise graphic of a phone.
Data
Technology
29 May 2024

How we use incremental modelling to handle billions of events every day

This post is an overview of how we leverage incremental modelling, a data transformation technique which helps us scale sustainably as we blast off to 10 million customers 🚀

Hero image with the text "How we built Year in Monzo - unlocking the data magic". Has an image of a blue smiley face and data being processed.
Data
20 December 2023

How we built Year in Monzo: unlocking the data magic ✨

Several months back, we got our heads together and started dreaming up Year in Monzo 2023. Here's the data team's story about how we get to where we are today.

Blog header that shows the text 'The SKAdNetwork Puzzle: Using Data to Solve for Effective Performance Marketing' with an image of puzzle pieces
Data
Technology
12 September 2023

The SKAdNetwork Puzzle: Using Data to Solve for Effective Performance Marketing

This blog talks through how Monzo uses Data Science and Analytics Engineering to measure the value of paid marketing as Apple’s SKAdNetwork changes the mobile advertising landscape, which helps to inform our wider strategies of sustainable growth

Sweating the Small Stuff: What do app screens and pedestrian-crossings have in common?
Technology
Data
20 March 2023

Sweating the Small Stuff: What do app screens and pedestrian-crossings have in common?

This blog talks about why app screens are like pedestrian crossings, or more specifically, how some subtle tweaks to a user-interface in Monzo's sign-up process has had a surprisingly large impact!

Moran Index on two features across UK
Data
Technology
2 March 2023

Designing a regional experiment to measure incrementality

This blog post covers the approach for how we designed a regional experiment to measure the incremental impact of our referral scheme on new customer growth.

Data
15 February 2023

Using topic modelling to understand customer saving goals

This blog post walks you through how we used a method called topic modelling to categorise Pot names into different themes so we can understand which Pots are used for holidays, life events, or just general savings.

Data
Machine Learning
Technology
19 December 2022

Machine Learning at Monzo in 2022

An end-of-year review of how machine learning continues to evolve and grow at Monzo

Data
Technology
17 May 2022

Joining Monzo as a Data Scientist

Izak joined Monzo as a data scientist in February. In this post, he shares his journey to Monzo and his early experience in the data discipline, with our data stack, and in the team looking after our Customer Operations.

Illustration of a Monzo card
Data
Machine Learning
12 May 2022

Moving from Data Science into Machine Learning

Rob joined Monzo as a Data Scientist, and recently moved into Machine Learning. Here's his journey!

Overview of Monzo's ML stack
Data
Machine Learning
25 April 2022

Monzo’s machine learning stack

Neal Lathia, Director of Machine Learning at Monzo gives an overview of Monzo's machine learning platform, the principles behind it, and future plans.

Data
8 February 2021

Borrowing Data at Monzo

We're hiring for the borrowing data team!

Data
Machine Learning
28 October 2021

Machine Learning at Monzo in 2021

A review of Monzo's machine learning team in 2021

Data
22 December 2021

How to think about the ROI of data work

Next time someone asks about data ROI, show them this formula.

Illustration of a laptop with a chart on the screen
Technology
Data
21 March 2022

Data hiring at Monzo: The interview process

We hire lots of different people in Data who join us to work in a lot of different teams. Our interviews are designed to do two things: teach you about Monzo and capture information that tells us the role is right for you.

Data
Technology
4 February 2022

How we validated our handling time data

We make lots of decisions based on data from customer support. We need to make sure we can trust this data. In this post, Niamh explains how her team validated the data.