Career Level Staff
Industry Research/ Development
Qualifications Bachelor's Degree
Day-to-day work includes:
– researching new privacy-preserving techniques that appear in the literature, and evaluating their applicability to real world use cases
– collaborating with the engineering team to build prototypes of new algorithms and early stage product ideas
– exploring the privacy characteristics of real world datasets and data systems
– reporting and educating internally on concepts from academic data privacy research, and internal research activities
– maintaining a connection with academia through meeting with our academic advisers and attending conferences
– meeting regularly with the policy team, and participating in policy events, to place new technologies in the context of legal and ethical privacy obligations
– focusing on the applied over the theoretical, research scientists at Privitar have the role of bridging the gap between academia and industry.
As a pioneer in privacy engineering, Privitar is positioned to establish best practices in industry management of sensitive data. As a member of the research team, you will play a role in helping to inform the company’s positioning, and product roadmap.
Our Research Culture
In the research team at Privitar, we are committed to tackling the hard problem of data privacy head on and are comfortable being challenged. We value creativity, teamwork, pragmatism, and hard work. We work together in small teams in a supportive way, developing our skills, learning from each other, and building on each other’s ideas.
- Masters or Doctorate degree in Computer Science, Mathematics or a Science or Engineering discipline.
- 2+ years of data science or research experience either in industry or academia.
- Some experience of coding in Python or equivalent.
- Demonstrable proficiency with mathematics and statistics.
- Experience with data visualisation and presentation of findings.
- Strong verbal and written communication skills.
Experience with data privacy techniques – for instance, homomorphic encryption or differential privacy