FELLOWSHIP

Kick-start your data science
career in just 9 weeks

Applications to our Spring 2025 programme will open soon

Sign-up for a reminder

The Faculty Fellowship gives the brightest STEM PhD
and master’s graduates, and postdoctoral researchers the skills needed to progress from academia into data science jobs. Across an intensive nine-week fully funded placement in London (UK), you’ll receive intensive training in both technical and commercial skills, and work on a data science project that has a real world impact.

Break into the competitive job market with expert-led training and work experience

The Fellowship begins with a two-week intensive training course, led by data science experts and commercial managers. You’ll have access to a range of cutting-edge data science tools and best practices, which you’ll then apply to a six-week placement with one of our host companies.

At the end of the placement, you’ll get the chance to present what you’ve achieved to industry experts at one of the biggest events in the Faculty’s calendar: Demo Day.

Add the full breadth of data science skills to your CV

Get training and mentorship from our data science team

Make your mark by working on a real data science project

Some of our host companies

The Fellowship doesn’t just set you up for your first data
science job; it unlocks lifelong career opportunities

The data science industry has never been so competitive.
But what we provide is an opportunity to crack the
data science industry with the requisite skills and
impressive work experience.

You will have access to our exclusive alumni community that’s brimming with over 450 ex-fellows who are already making waves in data science. You’ll network with industry leaders, uncovering new career paths well into the future.

The Faculty Fellowship gives you the expertise, confidence and credentials needed to secure your dream data science job.


95%+

of our fellows are hired by their
host company after the Fellowship

5 weeks

is the average time it takes
for a fellow to secure a job

1:1

mentorship from a technical
and commercial mentor

“Faculty provided a crash course in the skills I needed to succeed in industry, in an incredibly welcoming environment. It jumpstarted my data science career and I recommend it to every PhD who asks me about transitioning to industry.”

Archy de Barker
Head of Data & Machine Learning, Carbon Chain

“Taking part in the Fellowship was one of the best professional decisions that I’ve ever made as it helped me transition to data science and I haven’t looked back since. Since completing the Faculty Fellowship, I’ve worked in finance, real estate, maritime analytics and sustainability tech.”

Lyudmila Lugovskaya
Lead Data Scientist, Sustained

“Faculty was a landmark in my professional path and has represented the most important milestone in my career shift, transitioning from academia to a data science role. The Fellowship was very effective at providing necessary technical and soft skills as well as the confidence to be a successful data scientist.”

Enrico Deusebio
Chief Operating Officer, CGnal

The tangible benefits of being a fellow

Unlimited pizza and beer
on Fridays
Work from our super-swanky
London office
Cash your first data
science pay check
The chance to banter with the
best in data science
Go behind the scenes of
Europe’s leading AI company
Beef up your LinkedIn
with contacts from your
host company

Work on a real data science project within two weeks

See more Faculty Fellowship alumni present their commercial data science projects on our Youtube channel.

Break into the
competitive job market
with expert-led training
and work experience

We don’t have any specific entry requirements for the Faculty Fellowship. But we mainly look for PhD and master’s graduates, and post-doctoral researchers with some experience of programming, theoretical concepts of statistical learning and a high level of mathematical competence.

After the completion of the initial application review, qualified applicants will be invited to participate in a coding test.

Those that have passed the coding test will be invited to an interview with someone from our team, which is the final stage of the process before we offer places on the fellowship.


FAQs

When does the next fellowship begin?

We run three fellowships a year: spring (starting February), summer (starting in May) and autumn (starting in October). Applications close a couple of months before the next fellowship begins.
If you’d like to be reminded when applications open – and get more news on the Faculty Fellowship – you can sign up to our mailing list.

Do I have to have a PhD or masters – or be studying for one – to apply?

Generally, our fellows are drawn from two groups: PhD and masters graduates looking to transition out of academia, and experienced software engineers looking to move into data science. However, the most common qualifications for becoming a Faculty Fellow are:

  • A finished PhD in a STEM subject or a Master’s with some Machine Learning/Data Science experience.
  • A high level of mathematical competence.
  • The ability to code or have programming experience, especially in Python.
  • Some experience with theoretical concepts of statistical learning (e.g. hypothesis testing, Bayesian Inference, Regression, SVM, Random Forests, Neural Networks, Natural Language Processing, optimisation).
  • Experience with some coding libraries frequently used in data science.
  • The ability to communicate effectively with different audiences.
  • Experience composing and following a project plan/sticking to self-imposed deadlines/proactively solving your own problems.

So if you don’t have a PhD, masters, or software engineering background, but you do have other relevant experience that demonstrates these qualities, we’d still love to hear from you.

How much data science and software engineering experience do I need for this?

We don’t have a precise number of years of work experience in mind, but fellows should be able to demonstrate significant programming experience. Experience in maths or statistics is a plus, but not essential.

Do I need to be based in London for the programme?

Yes. The programme runs primarily from our London, UK office. Therefore, we do require fellows to be able to get into the office for most of the days for the duration of the programme.

Can I take two months off my PhD or job for this?

The Faculty Fellowship is intended to be a stepping stone to a new career, so we ask that applicants be available to start a job in London after the fellowship. If you’d like to join the Faculty Fellowship after your PhD or job wraps up, we’d encourage you to stay in touch by signing up for our interest list.

I’m currently studying for my PhD or masters – how can I stay up to date with the latest Faculty Fellowship news until I’m ready to apply?

If you’d like to be reminded when applications open – and get more news on the Faculty Fellowship – you can sign up to our interest list.

How is the fellowship structured?

Fellows receive two weeks of intensive lectures and workshops from experts in our Faculty data science team. The curriculum covers a wide variety of machine learning techniques, databases, distributed computing, data visualisation and a range of business skills. Following this, fellows begin a six-week project with one of our partner companies, solving a real business problem using data science and/or data engineering. Each fellow is assigned a Faculty mentor, who offers advice and guidance on both technical and commercial issues.

Do I need to have the right to work in the UK to join the programme?

Unfortunately, Faculty are unable to sponsor this role and you will need to have the right to work in the UK in order to be able to participate in the programme.

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