Education & Preferred Qualifications Bachelor's degree in a quantitative field with a minimum of 8 years of industry experience or PhD in a quantitative technical field with 4+ years of relevant industry experience. Direct relevant experience building models and analytics for cybersecurity, insurance, and other data intensive risk management related domains, structuring operational and log data in cloud native analytics environments. Demonstrated ability to work as an independent contributor driving research and analyses from conception to implementation with minimal guidance. Experience with scripting and data analysis programming languages, such as Python or R and advanced proficiency with SQL and data visualization tools Experience with cohort and funnel analyses, population clustering and segmentation techniques, and a deep understanding statistical concepts related to experimental design, selection bias, probability distributions, and Bayesian inference Experience answering unstructured questions, driving data-driven solutions, and managing projects and tasks to a conclusion Direct experience in the cybersecurity industry building analytics, models and detections (minimum 1-2 years). Ability to make difficult decisions in unique situations, present recommendations under pressure to senior leadership and to cross-functional teams that my have conflicting positions Demonstrated ability to identify core issues and work with leaders and team members to resolution Strong organizational, task switching, and prioritizing skills Ability to work independently and solve challenging problems while collaboration with stakeholders Advanced presentation skills, both orally and written Ability to work well with others and under pressure Demonstrated professionalism in approach to communicating ideas and solutions in simple language to team members, senior leaders and business partners