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Data Generalist

Sigma Software · Brazil · posted today ago

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About this role

WILL BE A PLUS

PERSONAL PROFILE

Are you passionate about solving complex data challenges beyond traditional Machine Learning models? We are looking for a Senior Data Scientist to join a newly forming team focused on improving large-scale analytics and detection systems within a cybersecurity product ecosystem.

As part of Sigma Software, you will collaborate with engineers, researchers, and analytics experts to simplify complex detection logic, investigate enterprise-scale data flows, and drive impactful improvements across production systems. This is a Full-time remote/hybrid opportunity for specialists who enjoy autonomy, systems thinking, and solving ambiguous analytical problems.

We at Sigma Software offer the opportunity to work on technically sophisticated products, influence analytical practices from the early stages, and collaborate with experienced international teams in a fast-paced environment.

CUSTOMER

Our Customer is a global cybersecurity company delivering enterprise-grade security and risk mitigation solutions for organizations and digital platforms worldwide. The company operates in a highly data-driven environment where large-scale signal processing, detection systems, and operational intelligence play a critical role in protecting users and businesses against evolving digital threats.

PROJECT

The project focuses on improving and simplifying a sophisticated analytics and detection ecosystem within the Customer’s Enterprise product line. The team works with complex rule-based detection logic and large-scale signal processing systems to identify redundancy, optimize data flows, and improve operational efficiency without compromising effectiveness.

This is not a Machine Learning-focused position. Instead, the role requires deep analytical thinking, engineering understanding, and the ability to investigate complex live systems independently. You will work closely with engineers, data scientists, and security researchers in a dynamic environment with rapid iteration cycles and evolving priorities.

Originally posted on Himalayas

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