In 2019, Nader Zentuti traded a promising academic career in Mechanical Engineering to embark on a data science journey with Faculty. As we commence our 22nd Fellowship cycle, Nader explains his experiences of the Fellowship, his career to date, and offers guidance to the next generation of Data Scientists.

“I spent most of my PhD thinking about a move towards data science. But after completing three degrees in Mechanical Engineering, it had become part of my persona. It wasn’t an emotionally-easy move,” remarks Nader, who has just celebrated his 2nd year at Faculty, now as a Senior Data Scientist. He had the opportunity to continue his academic career as a postdoctoral researcher, but credits the Fellowship for giving him the confidence to make the leap. “The Fellowship is not a one stop shop for all machine learning, but what it taught and ingrained in me was that I was capable of learning all of this, if I wanted.”

In 2019, mid-PhD, an email circulated in Nader’s university department encouraging applications and he took the plunge. “What sold me on the Fellowship was the people who underpin it. It had structure, and the interview process wasn’t a tick box exercise – it focused on me, and what I wanted to learn.”

In Nader’s view, the Fellowship framed machine learning as a ‘reusable, field-agnostic technology’ – a way of thinking totally different to what he was exposed to in academia. It offered the appealing belief that machine learning could be used in whatever way possible. For Nader, the Fellowship brought him to the other end of the spectrum to realise the vast applications of machine learning. Two months later, the prospect of returning to academia to apply machine learning to a ‘very niche engineering application’ had lost its appeal.

Developing new data applications

With the support of Faculty, Nader worked with a company to help predict the floor areas of UK properties, which is information valuable to utility, insurance and real-estate companies. Via the analysis of mortgage application data and Ordnance Survey maps, he built a machine learning model that estimated the square footage of a property via its address. 

“Property data isn’t openly available, yet so many businesses are after it – it’s core to the function of utility services and a goldmine for property investors,” explains Nader. “We had access to data on roughly 30-40% of properties in a given area but nothing that clearly stated ‘This flat on X road has Y total square footage’. But this is exactly what the project looked to solve – filling the gap of missing knowledge via data science.”

The Fellowship introduced Nader to the concept of abstraction – digging to the bare bones of a problem to generalise it, so that it becomes identical to another problem that has been previously solved. “We do this a lot at Faculty. The Fellowship quickly taught me to broaden my mindset to recognise that most problems fall into ‘buckets’ of problem types. I quickly learned that it is the skill of a data scientist to do that – bridging these gaps, and making solution-driven connections.”

From Faculty Fellow to Data Leader

Now as a Senior Data Scientist at Faculty, Nader reflects on the Fellowship as being a valuable introduction to the field, helping him to recognise data science as a tool applicable to a range of use-cases. “The Fellowship offers the tips of all these mini icebergs, making you aware of all aspects of data science that you may want to explore later on in your career,” Nader remarks, also noting that with the range of opportunities available, his interests – and understandings – quickly changed. “I learned about Bayesian Modelling for example, and it went mostly over my head. But two years later, I’ve gone back to my Fellowship lectures to brush up on the main concepts, paving the way for me to build a model for one of our clients.”

Nader considers the Fellowship as a key to discovery, with data science applicable in a range of fields from healthcare to government. With the accelerated interest companies have in developing AI teams, he feels that data science is a real door opener. As Nader rightly notes, “There’s plenty of companies across all sectors in the economy looking for data scientists so there’s real flexibility to pursue your passion.”

For Nader, his passions led him to a full-time role at Faculty and he has since progressed to the title of Senior Data Scientist. Having evolved from purely technical work, he now heads up the planning and management of multiple projects. “I’ve developed both technical skills and ‘soft skills’ – management experience and client engagement. It has done wonders for my career progression, and part of my role now is to guide other data scientists to achieve the best work they can.”

With a focus on empowering others, Nader reflects on the community feel of Faculty and the power of the Fellowship for new entrants to the field: “Coming from academia, you feel very isolated – you have a certain view towards your field, and about your career. But when you come to Faculty, you find a cohort of people feeling exactly the same as you. You can see what your future career could look like, and it gives you a bit more ‘artistic inspiration’ – a real taste of what you could do with your career. The people are genuinely nice, and we’re all like minded. It’s very much like a village…”

About Faculty Fellowship

To learn more about our Fellowship programme, its history, and how to apply, visit our Fellowship webpage.

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