Sometimes we forget the humans behind the tech in our ever busy world. DSF is fortunate enough to know some incredible tech leaders across the world and has the privilege of hearing them present at our events. That being said, our Speaker Spotlight sets the stage to get to know our speakers on a more personal level and connect them with our growing community. Read the mini interview below!

A bit about Louisa:

Louisa is the Lead Data Scientist at Virgin Red, where she leads the team’s work in building tools and data products such as their recommender system and propensity models. She also works with teams across the business to promote Data Science and develop new opportunities together. Having previously worked for four years at Trainline, Louisa is passionate about creating models and products that have a real, positive impact on customers’ lives.

How did you start out in your tech career?

My career actually started off down a totally different path. My first job out of university was as an acoustic consultant, as I wanted to link my Physics degree with my love of music, however I realised it wasn’t quite right for me and that I missed the problem solving aspect of my degree. This was at the time that Data Science was just becoming popular, so I took a bit of a leap of faith and enrolled myself in a Data Science Masters – the first year my university had run it. The rest is history, I loved my course and ended up finding my first job as a Junior Data Scientist.

What are the signs of success in your field?

I think it’s about building models that actually make it into production, and seeing your work out there powering a website, app or email campaign! So often as Data Scientists we focus all our attention on developing a model but equally important is working with other teams, focusing on how what you’ve built is going to be used and impact your customers or company.

What is the best and worst thing about your job role?

I love the huge variety in places Data Science can be applied. Being able to have an impact in different areas of the company means I’m constantly working with new people and learning new things. And I know that in the future, if I wanted a change, I could take my Data Science skills to a totally different business and would find a completely new set of projects and challenges.

There’s nothing I really dislike about the role, but I have to admit the testing process that you have to go through to check everything works once you’ve built a model and before you can deploy it can be quite painful!

What can you advise someone just starting out to be successful?

Get involved in as many opportunities as you are able to, and try to speak to as many different people as you can. Not only will you get lots of different viewpoints, it may open up doors later down the line. Nothing can beat experience.

How do you switch off?

I’m very lucky to live near to the countryside, so a weekend with a long walk and a pub at the end is pretty perfect for me.

What advice would you give your younger self?

As above, get involved in as many opportunities as you can. But also, figure out what you love doing and really explore that. You’ll perform so much better at something you enjoy than something you hate, and the reality is, you’re at work for too many hours of your day to be doing something you don’t like!

What is next for you?

At the moment, my biggest focus is on building out our Data Science team and capabilities here at Virgin Red. We’ve got some solid foundations but there is so much more I think we can achieve in the future, so watch this space…

If you could do anything now, what would you do? Why?

Personally, we’ve been renovating our house for the past two years, and it feels never ending. If I could wave a magic wand and it all be finished, that would be pretty good.

What are your top 5 predictions in tech for the next 5 years?

Judging by the last five years, I don’t think any of us can accurately predict what’s coming next, but in the near future I think we can expect:

  • ML/AI will continue to become a lot more accessible for everyone, however skilled, to use and train
  • Ethics will become ever more important as new AI developments come about
  • The role of the Data Scientist will adapt and continue to split out into more specialist roles, like we’re already seeing with ML Engineering
  • LLMs and Gen AI will be everywhere
  • The robots won’t have quite taken over, just yet…

Watch Louisa’s session at the Data Science Festival here.

Thank you to all our wonderful speakers for taking part in our Speaker Spotlight

Want to become a DSF Speaker? Apply here!