Data Science Graduate Programme


Have you ever wondered how Amazon knows to recommend the phone charger you just broke? Or how Spotify knows what song you want to listen to next?

Do you ask yourself questions like: are the stumpy trees good enough? How can I stop my ReLUs from dying? Is this NP-hard? The RNNs are discriminative enough, but what have we learned?

If so, we would love to hear from you!

We are looking for curious graduates who want to go beyond the algorithms, to solve complex real industry problems that will accelerate the growth of our ventures and transform industries.

The Data Science Programme is an 18-month programme where you join the team of one of our early stage businesses and earn an MSc in Data Science qualification simultaneously. During this time, you will …

  • Solve big industry problems. You’ll work on projects where you’ll need to assess current business problems, investigate business needs, apply data science techniques to real life problems and implement solutions. Some of the problems you might be working on involve how natural language processing can categorise content or how to use AI to build a music talent discovery platform.
  • Work in an early-stage business environment. In large corporates, it’s easy for graduates to be swallowed up and not see the impact of the work they’re doing. In an early stage business environment, it’s quite the opposite. You’ll get huge exposure to how tech companies are built and be supported while taking ownership of work that really matters. You’ll learn how to develop solutions in a fail fast and safe environment that focuses on developing transformative innovation.
  • Become tomorrow’s leaders. You won’t just become a Data Scientist; you’ll develop the business analysis and entrepreneurial skills to apply your solutions to real life problems and deliver meaningful change. This is a great opportunity to build your career in one of the most exciting and watched fields in the world - learning from true innovators, in a fast paced, dynamic environment.
  • Learn from industry experts. We’ll train and support you on business-building approaches, and how data science can be applied to grow businesses. You’ll be trained in advanced engineering and machine learning. This will be taught by our highly qualified Data Scientists via lectures, seminars and hackathons. On top of that, you’ll receive a MSc in Data Science qualification on completion, accrediting you with core business and analytical skills.

A career within the BC Ventures isn’t like any other career. You’ll be joining a network of people working together to make a difference in their industries. We’re proud of the community of brilliant people we’re building; we believe it’s our strongest asset.

You will have the following technical requirements:

  • A degree in a STEM discipline such as Mathematics, Applied Mathematics, Statistics, Theoretical Physics, Experimental Physics, Computer Science, or BSC (First Class or Second Class Upper Only), MSc, PhD
  • Some experience with at least one programming language such as R and Python (desirable) or C, C++, Java, Scala, JavaScript, MATLAB (acceptable)

Successful Data Scientists are not only good at creating algorithms and managing large data sets, but also at communicating and understanding people’s problems. That’s why we have a set of values that guide who we hire, and how we approach data science:

  • Never stop looking for a better way of doing things; be curious
  • Understand what people need, look beyond what they say; be empathetic
  • Visualize what does not exist yet; be creative
  • No one has all the solutions, be a team player/partner with others to find them; Embrace collaboration & partnership

To apply please follow the link and submit your CV along with answering the following questions:

  • At BC we look for curious people. Tell us in a few lines about a time during work/university where you found a better way of doing something?
  • Tell us briefly about your biggest personal or work achievement?

Closing date for applications is the 10th January 2020.

In the meantime, make sure to connect with us on Twitter, LinkedIn, Facebook.

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