We are your data science workshop.

Data Scientist/Senior Data Scientist

Data Mettle Data Scientist London Recruitmenmt

What we are looking for

  • An inquisitive individual with the ability and eagerness to constantly learn and teach others.
  • Master’s or PhD degree in a highly numerate subject, for example machine learning, statistics, bioinformatics, physics or applied mathematics.
  • Solid understanding of statistical methods and ideally some experience with optimisation and machine learning methods.
  • Expertise in programming languages such as R or the Python scientific stack (NumPy, SciPy, scikit-learn, etc.).
  • Business acumen. An ability to understand customer requirements, how our solutions will work in situ and how they will be successfully embedded to deliver value.
  • A natural collaborator, who will partner with our customers and reach out to the data science community to share insights and knowledge.
  • Self-starter with strong analytical, critical thinking, and problem solving skills.
  • Excellent communication skills — ability to present complex information in a concise and compelling manner.
  • You’re the sort of person who’ll enjoy the challenge of being involved in the growth of an early stage tech start-up.


  • Apply quantitative techniques to cleanse and explore large (and small), complex data sets in preparation for further analysis.
  • Apply your knowledge to find practical solutions to our customer’s diverse challenges.
  • Meet with customers to work out use cases and key requirements.
  • Stay current with new data science methods, technologies, and industry trends.
  • Work with the team to develop and implement data science processes and best practices.

Who we are

We are a small but growing company, and we are working to establish ourselves as a leader in data science. We have a diverse customer base that means our team get to work on a variety of interesting and complex data projects. We deliver great products and we tell people about it – our customers, our community and the public.

We care about our people and promote working arrangements that allow flexibility and work life balance. Our customers are our partners, we listen to them, again and again. We work with them in an agile way to facilitate collaboration, continuous feedback and learning.

What we offer

  • Competitive salary
  • Private health insurance
  • Flexible working arrangements
  • 25 days annual leave
  • £5000 annual training budget
  • ½ day each week for side projects, learning and experimentation

How to apply

Send a CV and a short paragraph on why you’re interested in this role (please no more than 300 words) to jobs@datamettle.com by April 13.

Data Scientist Unicorns Recruitment Guide

Recruiting data scientists can be a big challenge. Often companies are keen to employ good people who know how to make the best use of their data, but don’t know how to choose them. We’ve put down our thoughts into this data scientist unicorns recruitment guide:

What makes recruiting data scientists difficult?

A lot of people are unclear about what it is exactly that data scientists actually do. Certainly, this must make things harder for the recruiter. However, other factors make recruiting harder too:

  • The terminology is unfamiliar.
  • Interview panel members may not know how to test candidates on their knowledge.
  • Not all data scientists are the same. Some have particular strengths in mathematics and statistics, others are software engineering pros, many are expert in analytics and business intelligence. How do the candidates in front of you match your needs?

What can you do to make things easier?

In my opinion, data scientists should be among the best communicators in the tech sector. After all, their job is to take your large, complex data sets and produce easy to understand results. This means they should be able to state clearly what their skills are and how they relate to your needs. But that’s only a start: how can you be confident that you’re making the right hire?

Don’t be intimidated

If a candidate uses unfamiliar terminology, ask them to explain what they mean. Dig down into their knowledge. Some examples might be

  • You’ve mentioned some algorithms. Can you explain to us under what circumstances you would use each of those, and when and why they might need to be avoided?
  • What are the underlying assumptions for those techniques? Are there any mathematics or statistics you could discuss to justify them?
  • Can you discuss the advantages and disadvantages of those packages? In terms of accuracy? Performance? Amount of data required for training? Time required for training?
  • How would that be implemented? Can you write some code on the board.

Even if you don’t know the answer (and why should you? That’s why you’re employing them) good candidates should be able to explain these sorts of things, and it will be obvious if a candidate is struggling to answer.

Simple can be better

Simple technical questions can be surprisingly good at testing candidates. I like to use short maths or programming tasks that are related to an everyday problem. It’s surprising, but these sorts of questions can work really well at establishing a baseline for more in depth questions. (Of course, you probably need someone on the panel who can answer these questions, if you decide to use them)

  • Let’s say you have a list of people’s names and their birthdays. Can you write a programme, in any language, that returns a happy birthday message if it’s somebody’s birthday today?
  • There are a whole lot of simple maths or statistics questions on the internet that you could use. It’s usually worth adding a bit of a twist to these questions, in case they’ve already seen them.

In short, I believe it’s a good idea to try to dig deeper, ask for clarifications, or other solutions.

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