Data Modeler

A growing cyber-focused team is hiring multiple Data Modelers to help design and evolve predictive models that support insider risk detection and analysis. This work goes beyond traditional reporting or static statistical modeling and focuses on identifying dynamic patterns, behavioral interactions, and emerging risk signals across large-scale data environments.This role is ideal for someone who combines strong coding ability with advanced quantitative thinking. You will work across raw and metric data, contribute to model development in distributed environments, and help shape how modern behavioral and predictive modeling is applied to complex enterprise risk challenges.What You’ll TackleBuild and refine predictive models that support insider risk and cyber-related use casesWork across raw and transformed datasets to develop meaningful model inputs and outputsAnalyze dynamic behavioral patterns and interaction-driven signalsContribute to AI/ML workflows in a modern distributed data environmentDevelop and test model logic using Python, PySpark, and related toolsPartner with technical teams to support scalable model developmentHelp shape emerging approaches to behavior-based risk detectionOperate within Databricks and distributed processing frameworks to support advanced analyticsWhat You BringStrong computer science or technical engineering foundationExperience developing predictive or behavior-driven modelsProficiency in PythonWorking knowledge of Java is a plusHands-on experience with Databricks and PySparkExposure to distributed data processing and scalable analytics workflowsBackground in AI/ML, data science, and applied statistical methodsAbility to work with complex datasets and ambiguous problem spacesStrong problem-solving skills and comfort with evolving model designAbility to explain technical concepts and modeling decisions clearly