Responsibilities
Create rules and models to broaden repertoire of sensitive data classes, from knowledge acquisition to writing production code.
Define success metrics for classification performance. Use those to measure, monitor, and evaluate results. Help set the standards and constantly raise the bar.
View, extract, analyze, label, and present data from multiple organizations, different cloud environments, storage technologies, interfaces, and formats.
Create processes and tools that will allow non-technical stakeholders to have a clear view of scanning and classification KPIs.
Make the most of our enormous amounts of data to help drive product and R&D decisions.
Work from within the R&D Data team, take part in the discussions revolving around data science objectives, priorities and solutions.
2 years of hands-on experience analyzing data – a must
Proficiency working with SQL, Spark or similar technologies – a must
Basic programming and related skills, e.g. Python, git
Degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics
Basic understanding of descriptive and inferential statistics
Can-do attitude, problem solving skills, self-starter, proactive mindset
Previous experience in the cybersecurity domain – an advantage
Experience with cloud environments – an advantage