Delivering bespoke, state-of-the-art technology solutions for big retail companies is not quite what Starcount’s Senior Product Manager Chris Nourse had envisioned in his childhood. Read the interview to find out more.
What brought you to Starcount?
I love working with data. Previously, I had been an analyst and product manager in business intelligence – so a chance to work with pioneers in the industry was a massive selling point. What really sealed the deal was seeing The Observatory in action and learning about how the wealth of information it contains was brought together and turned into something so attractive.
Tell us more about what your role is at Starcount.
As Starcount’s Senior Product Manager, I spend my time scoping, prioritising and planning the features that will go into our products, Observatory and Audiences. This involves writing (use cases, specifications, project plans, etc.) organising meetings to ensure the information gets to the right people and plenty of tweaks to get the latest release ready (design tweaks, analysis and testing). All of this with the goal of making sure that our designers and developers are building the right solutions for Starcount’s users.
What has been the best moment in your career to date?
The release of Audiences, Starcount’s second product. Audiences was the first product I managed for the entire journey, from the initial idea to the market-ready version. The satisfaction of building something from scratch is amazing, you really become attached to it. Is it weird to feel attached to a web app?
What is the most exciting project you’re working on right now?
In a data science workflow, the most arduous part is typically the preparation of data and within the preparation of data, the most arduous part is often the labelling of it. We are currently working to replace a crucial labelling step, previously performed by hand (many hands really, over many days), with an automated ML (machine learning) approach. It’s exciting enough to use machine learning to solve such a difficult problem but, even more exciting, the results are startling and we’re on track to drastically improve the speed and accuracy of our labelling.
What did you want to grow up to be when you were younger?
A winemaker. I grew up in Cape Town and found vineyards to be very beautiful, relaxed places filled with people in the best mood. It was only later that I learned that making wine is an extremely stressful profession and wine-drinking was the reason for everyone’s good mood. I’ll stick to visiting vineyards.
What do you think gives Starcount a competitive advantage in the current market?
Within Starcount, we have a deep knowledge of the data sources that are best placed for solving our client’s problems. Additionally, we have a unique mix of technical expertise in data science and product development. This blend of ingredients has allowed us to build data pipelines and products around tailored solutions and scale them to enterprise level quicker than anyone else. In short, we excel at solving problems with data – our competitive advantage is our expertise in hardening those tailored solutions into products and services at speed.
What do you love most about Starcount?
Starcount provides the autonomy to explore new ideas. There is an openness to new concepts, technologies and techniques and (as long as it contributes to the business and isn’t something like a crypto mining tool) there is space made to test prototypes. It means that everyone can have a bit of much-needed R&D in their role.
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