About the roleWe are looking for aSenior Data Scientistto develop predictive models and quantitative analytics that power risk-based vulnerability prioritization within a large-scale enterprise security program. You will structure and analyze massive security telemetry datasets, build ML algorithms to eliminate scanning noise and false positives, and establish unified data dashboards to drive adoption of data-driven security governance. The role requires 6+ years of data science experience applied specifically to cybersecurity, vulnerability management, or financial risk models.
ResponsibilitiesDevelop predictive models and quantitative analytics to prioritize vulnerabilities based on contextual risk and business impact;
Structure and analyze massive outputs of security data from across the enterprise ecosystem to support the ASPM framework;
Create machine learning algorithms or statistical models to automatically identify and filter out scanning noise and false positives;
Establish a unified data delivery structure and dashboards to drive the adoption of data-driven security governance.
MUST HAVES6+ years of commercial data science experience, operating completely autonomously with no required supervision;
Advanced proficiency in Python, R, and SQL;
Experience with machine learning frameworks (Tensor Flow, Py Torch) and data visualization tools;
Prior commercial experience applying data science specifically to cybersecurity, vulnerability management, or financial risk models;
Upper-intermediate English level.
NICE TO HAVESFamiliarity with Cloud Security Posture Management (CSPM) data outputs (e.g., Wiz).
PERKS AND BENEFITSProfessional growth: Mentorship, Tech Talks, and personalized growth roadmaps.
Competitive compensation: USD-based pay with education, fitness, and team activity budgets.
Exciting projects: Modern solutions with Fortune 500 and top product companies.
Flextime: Flexible schedule with remote and office options.