Ellie details out various parts of her journey as a particle physicist and her path to Data Science at Arundo.
Ellie details out various parts of her journey as a particle physicist and her path to Data Science at Arundo
HOUSTON, USA – Last month I was in Houston getting to know some of the new hires in the data science team and it turned out that one – Roy - is the organiser of the Houston Data Science meetup which we are now hosting in the Arundo office location (Station Houston). I attended the meetup to share some observations I have from my career in IOT analytics.
At the meetup Roy did a round table introduction and what struck me is that most of the people in the room (out of a crowd of about 60) were engineers who were either transitioning or considering a transition to become data scientists. Good news for us at Arundo who are always looking for data science hires with Oil and Gas backgrounds!
Not my background, though. I head up the data science team at Arundo and have worked in quite a few different industries before ending up in this role –none of them Oil and Gas based. I spent several years working as a particle physicist at CERN for several years on the LHC experiment (which can be thought of as a large bundle of sensor data, at least from a data scientist perspective). I subsequently spent the next few years working for a couple of tech companies in a data scientist role - effectively building predictive models in industries as far removed as fashion analytics and Formula 1 racing.
The upside of having seen many different industries is you develop pattern recognition on how to tell a story from data as opposed to from the system that generates the data – in short, a data science approach instead of an engineering one. However, we in Arundo believe that the magic lies in being able to combine these two approaches and are thus hiring people from both sides of the table.
In our customer engagements, we have found that getting to the right use case is a real challenge in IOT analytics, as you not only have to find the sweet spot between data science and engineering, but also have to consider feasibility and business value. We believe in Arundo that an agile workflow is essential in quickly finding the right use case and aim to fail fast and with pride on use cases that aren’t going to fly. We are developing our software products to support this workflow right from data ingestion through to a one-click model deploy.
We discussed this with the crowd at the meetup and the need for a quick and iterative workflow really seemed to resonate with people. All in all it was a great meeting, super crowd, nice pizza and I’m looking forward to my next visit.