About Fetch Analytics



Company Size


What we do

Fetch provides real-time, insights on how people interact with the physical world.

Location insights provides users with a real-time, cost effective, bespoke solution to help understand current and historic changes in dwell time, popular locations, visitor preferences, engagement, space usage, visitor patterns and pedestrian journeys.

Fetch Analytics is active in 5 markets – UK, Sweden, Spain, Netherlands and South Africa.

How it works

We sit at the intersection of data science and software engineering. Being a location analytics company, the data science and algorithmic work is largely in the geospatial realm. We've got a lot of data. Hundreds of billions of rows. The data processing is done using Q/KDB on Google Kubernetes Engine (GKE), using a container workflow orchestration framework - Argo Workflows.
The subsequent artefacts which are created by our algorithms are then served up (via GraphQL) on a Django/React stack.

Why Work For Us

You'll be exposed to our bespoke data pipeline which processes hundreds of *b*illions of rows of data. The pipeline is run in Argo Workflows over a columnar, time series database called KDB, the language of which is called Q.
The actual data analytics/science work can be done in whatever language you feel is appropriate :).

Our Culture

We're independent thinkers who value collaboration. We meet once a day at 12PM SAST and describe what each of us is working on. That way, if one of us is stuck, others can provide insights. It's generally a brief meeting (not more than 20 mins). Team members can then meet with each other after the meeting if needed.

Our Engineering Processes

We're a small technical team. 3 of us so far. The upshot is that each of us needs to be well versed in multiple aspects of our overall tech stack.

For example, if you're applying for the data science position, then it's worth noting that we don't have a data engineering team. Heck, we don't have a data engineering person. As an example, this means that a successful analytics/ data science project may require writing your own Docker image. It happens.

Having said that, it's important to note that we're very supportive of one another. Each of us has their own mixed bag of skills and we're always learning!

Upskilling for us isn't a nice to have; it's a necessity.

Our Hiring Process

This is what you can expect when interviewing with us.
Our interview process has the following stages:

Initial meeting - tell us a bit about yourself, how you got to where you are (1 hour).
We tell you about the company, what's expected, etc.

If the initial meeting is successful, then there is a second, technical meeting (1.5 hours).

Finally, there is a technical assessment. You can use whichever language you like for it.

A bit more about the technical assessment:
It's a data challenge. We give you data germane to our business and you answer some questions about the data :)

During the process, you are likely to meet the following members of our team:

Orry Messer - CTO
Dean Money - COO

How to make a good first impression:
Be open, honest, and intellectually curious!

How long does our interview process usually take, from first call to offer stage?
Can be as quick as a week if things go smoothly.

If you need any additional information on our interview process, please reach out to us directly.
Alternatively, please take a look at our careers page to get to know us better.

Global Exposure
Flexible Hours
Remote / Hybrid
Tech Stack

Application and Data

Google Cloud Platform