Description of the job
A vacancy for a data analyst with machine learning expertise (m/f) in Airbus Cyber security Defence Centre has arisen within Airbus (Commercial Aircraft) in Getafe. You will join the Cyber Security Department.
About Cyber Security is Airbus:
Security is not an option, be part of it!
Today, governments, companies and private individuals are increasingly the target of attacks like theft of intellectual property, sensitive information and even money.
Last year Norton Cybercrime Report estimated a global cost of cybercrime around 150 billion Euros.
Airbus Group is more and more at risk due to its leading position in the market and the additional risks coming from the Extended Enterprise. We have been facing malware attacks which have become more and more sophisticated over the last months.
IT Security measures can do a lot, but each of us, as Airbus employees, are the first line of defence.
What is doing the Cyber Security Defence Centre team:
Security threats have increased drastically in the last few years and organization are facing an increasingly complex threat landscape. Airbus digitalization is bringing many opportunities but they come with new risks. Therefore, Airbus has developed state-of-the art cyber-threats detection capabilities, relying on more than 10 years of experience, in order to protect its business assets.
Why do we need Insider Protection in Airbus:
Traditional enterprises identity based on username and password based credentials with a safe perimeter.
As perimeter concept weakens, we need to track user behavior, context (activity, location etc) and device trust, as additional means of risk based user authentication.
Your role as an Experienced Data Analyst will be coordinate the data analyst & Data wrangling activity activity and to report it to the Insider protection product manager.
You will also have to examine data closely to reveal trends, patterns and actionable intel.
You will lead analysis projects from start to finish including all aspects of data analysis (e.g. processing, cleaning, verifying the integrity of data used for analysis, statistical analysis, visualizations) and communicating results.
You will also participate to the set-up of machine learning capability to detect insider threats abnormal behaviors.
You are based in Getafe with regular travels to Toulouse and report to the Insider protection product Manager.
Tasks & Accountabilities
As the successful candidate your main tasks & accountabilities are:
● Participate to the set up a Machine Learning platform and framework
● Develop detection rules that will allow us to reveal insider threat anomaly
● Ensure the delivery of analysis project end to end from the anomaly case study to the final result analysis restitution into the dashboard and visualisation tools.
● Contribute to the evolution and improvement of the Insider Protection product framework
This role will involve regular travel to Toulouse and as such you must be able to travel accordingly.
We are looking for candidates with the following skills and experience:
● Master’s Degree specialised in Information Technology (or equivalent),
● Experience on Cybersecurity and/or fraud data analysis is a plus
● Capacity to transcript from business demand to data models
● Experience in team leading
● Knowledge and experience of machine learning and deep learning, supervised and unsupervised learning, behavioural analysis algorithms, Bayesian inference, statistical modeling
● Good knowledge of scripting languages (e.g. Python, Java), Statistical computing packages, (e.g. R), databases: SQL, Graph databases
● Good knowledge in data collection methodologies, log management, data wrangling
● Capacity to set up scalable & agile platform and optimized data model to collect, handle, compute and visualize data.
● Knowledge and experience in SPLUNK Enterprise Security
● Experience for cloud platform (G-Suite, AWS, ServiceNow
● Agile mindset required, experience in Agile, SAFE & Scrum methodology preferred but not essential
● Fluent in English. Advanced level in French would be appreciated.
Please apply for this vacancy with your CV attached.