About the job
About Galvanick
Galvanick is at the forefront of cybersecurity, dedicated to safeguarding the industrial sector from cyber threats. Our innovative threat detection platform is designed to protect Operational Technology (OT) systems and networks from both criminal attacks and state-sponsored threats. Join a dynamic startup environment where passionate professionals work collaboratively to tackle significant cybersecurity challenges. We are proud to be supported by leading investors such as Founders Fund, Village Global, and MaC Venture Capital.
About the Role
We are on the lookout for a skilled Data Scientist & Developer to join our team. In this hybrid role, you will collaborate with cybersecurity experts, enhancing their analytical capabilities. You will contribute directly to our mission of securing national infrastructure through advanced analytics and software development to identify cyber threats affecting critical systems. This position offers a unique opportunity to apply your data science expertise while actively engaging in coding and enhancing our production codebase.
Your responsibilities will include analyzing complex security datasets, developing analytical tools, and supporting our detection engineering processes. If you are eager to simplify challenges and provide effective solutions for our customers, we would love to hear from you.
What You Will Do
* Collaborate with Detection Engineers to translate detection needs into data and analytical tool requirements.
* Enhance our data platform and develop tools that fulfill those requirements.
* Create methods to assess detection accuracy and minimize false positives.
* Design data models to identify behavioral patterns indicative of cyber threats in OT settings.
* Conduct exploratory data analysis on security incidents to reveal hidden correlations and attack strategies.
* Generate key metrics and KPIs to evaluate detection effectiveness and data utilization; provide insights on data pipeline enhancements and integration of new data sources.