• Analyze and investigate existing detection logic built on multiple interconnected signals and rule-based expressions
• Understand and map complex data flows, processing pipelines, and dependencies across enterprise systems
• Identify redundancy, inefficiencies, and unnecessary complexity within current detection structures
• Propose simplification and optimization approaches while preserving detection quality and operational effectiveness
• Conduct exploratory analysis on large and complex datasets to validate hypotheses and support decision-making
• Assess downstream implications and operational risks of proposed changes before implementation
• Translate analytical findings into clear recommendations for technical and non-technical stakeholders
• Collaborate closely with engineers, data scientists, and security researchers to gather context and resolve blockers independently
• Operate effectively in a fast-paced environment with shifting priorities and short delivery cycles
• Contribute to improving analytical methodologies and approaches within the newly forming team

• 5+ years of experience in Data Science, Analytics Engineering, Data Analytics, or related analytical roles
• Strong proficiency in Python and SQL
• Experience working with large-scale and complex datasets
• Strong analytical and problem-solving skills with the ability to independently structure ambiguous problems
• Proven experience driving investigations from hypothesis generation to data-backed conclusions
• Strong engineering mindset with the ability to understand and reason about complex logic and codebases
• Ability to evaluate system behavior and understand downstream impacts of analytical decisions
• Experience collaborating cross-functionally with engineering and research teams
• Ability to work autonomously with minimal supervision
• Upper-Intermediate or higher English level
• Familiarity with JavaScript

WILL BE A PLUS

• Experience with Snowflake
• Experience in cybersecurity, fraud detection, or risk analytics domains
• Experience working with rule-based systems or detection pipelines
• Exposure to enterprise-scale analytics platforms
• Understanding of data pipeline architecture and signal processing systems

PERSONAL PROFILE

• Independent and proactive problem solver
• Curious and investigative mindset
• Comfortable working in ambiguous environments
• Strong ownership mentality
• Adaptable to changing priorities and fast delivery cycles
• Collaborative and communication-oriented
• Detail-oriented with strong systems thinking capabilities

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.

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