Job Description

ABOUT THE ROLE

We are looking for a Senior Data Scientist to 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 5+ years of data science experience with direct commercial application to vulnerability management, operating with full autonomy.

WHAT YOU WILL DO

- Develop 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 HAVES

- 5+ 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, including TensorFlow and PyTorch;

- Experience with data visualization tools;

- Commercial experience applying data science specifically to vulnerability management;

- Upper-intermediate English level.

NICE TO HAVES

- Familiarity with Cloud Security Posture Management (CSPM) data outputs (e.g., Wiz).

PERKS AND BENEFITS

- Professional growth: Mentorship, TechTalks, 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.