Use data for machine learning and data science, while also protecting privacy

Data Science, machine learning, and the smart use of data can change the world for the better. But most interesting data is about people, and it's important to respect the privacy of the individuals in the data. This applies to your banking data, your phone records, health data, mobile phone locations, etc.

At Privitar we're developing Privacy Engineering software - products to enable the principled use of data, while ensuring that confidentiality is protected. We work closely with academia and industry to translate the latest techniques in data anonymisation, differential privacy, homomorphic encryption and secure multiparty computing into products that companies can use and understand.

Our interview process

We believe that if you hire really great people, everything else becomes easier and more fun. So we invest time in the interview process - our process looks like this:

1. An introductory call to tell you about Privitar and learn about you and what you're looking for

2. A practical test - for backend developers only. This will be a coding test. But we make it interesting and relevant, so you get a flavour of the kind of work we do

3. A 1/2 day of face to face interviews, covering coding, technical questions, learning about your experience and your ambitions

4. Offer

Interviewing is a genuine two-way activity - we want to know if you have what it takes to succeed at Privitar, but also to make sure that you get to know us and can decide whether we're the right company for you. We're still quite a small team, so you'll meet most of the team during the process. We'll also try to be flexible, as we know that it's not always easy to schedule interviews, and we can move fast and combine stages if you're up against a deadline.