Role: Data Scientist
Reference: KEEP04
This role is part-funded by the ERDF

Anon.ai is a cyber security automated data anonymization tool using AI driven technologies. Anonymising data is a regulatory requirement according to data driven policy, but it’s often an operational expense. At Anon, we believe that anonymising data is a problem that the computer should be able to solve for you. Our software is smart enough to make intelligent decisions based on a synthesised understanding of content, structure and context. You should be able to just express your intentions and let the system take care of applying them – accurately and this is founding principle of Anon’s platform.

Whilst our priority is to help our customers become GDPR compliant, and so anonymisation is crucial – but in turn we must ensure that anonymising data doesn’t remove any useful insight for this data. We adopt state of the art machine learning algorithms to ensure that data is useful and insightful to our customers whilst ensuring that they are GDPR compliant.

We are seeking a data scientist to work on an exciting project designing a new type of automated classification system that fuses best in class topological, contextual data analysis and NLP processing algorithms. This system will be able to understand both structural and contextual information that existing automated systems can’t handle.

Basic Qualifications

• MSc/PhD in Computer Science, Data Science / AI or Machine Learning (or other quantitative discipline) from a top instituion
• Solid understanding and experience of implementing Machine Learning algorithms
• Well rounded knowledge of ML/statistical concepts around (regressions, classifications, decisions trees and neural networks)
• Solid understanding and experience implementing NLP based solutions
• Experience of preparing , processing and analysing large data sets
• Expert use of Python (numpy, scipy, pandas, nltk, TensorFlow, Keras, Theano etc.)
• Experience working within multidiscplinary software engineering teams using collaborative tools such as git
• Experience of using cloud ML resources
• Eager to learn new technologies and ability to integrate with other developers across the entire stack

How to apply: Send your CV and covering letter to capai@capitalenterprise.org with the reference “KEEP04” in the subject line.
Issue date: Monday 2nd October 2017
Closing date: Friday 13th October 2017