Develop predictive models and analytics to prioritize vulnerabilities by contextual risk and business impact. Structure and analyze large security telemetry datasets, build ML/statistical models to remove scanning noise and false positives, and create unified data delivery and dashboards to support ASPM and data-driven security governance.
AgileEngine is an Inc. 5000 company that creates award-winning software for Fortune 500 brands and trailblazing startups across 17+ industries. We rank among the leaders in areas like application development and AI/ML, and our people-first culture has earned us multiple Best Place to Work awards.
WHY JOIN US
If you're looking for a place to grow, make an impact, and work with people who care, we'd love to meet you!
ABOUT THE ROLE
We are looking for a Senior/Lead 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 6+ years of data science experience applied specifically to cybersecurity, vulnerability management, or financial risk models.
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
- You must be authorized to work for ANY employer in the US (e.g., Green card holders, TN visa holders, GC EAD, H4 EAD, U4U with EAD), as we are unable to sponsor or take over employment visa sponsorship at this time;
- 6+ 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 (TensorFlow, PyTorch) 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 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.
Similar Jobs
Software
Develop predictive models and analytics to prioritize vulnerabilities by risk and business impact. Analyze large-scale security telemetry, build ML/statistical models to remove scanning noise and false positives, and create unified data delivery and dashboards to enable data-driven security governance.
Top Skills:
PythonPyTorchRSQLTensorFlow
Software
Lead development of predictive models and analytics to prioritize vulnerabilities by contextual risk, analyze large security telemetry datasets, build ML/statistical solutions to remove scanning noise and false positives, and deliver unified data structures and dashboards to enable data-driven security governance.
Top Skills:
PythonPyTorchRSQLTensorFlow
Software
Develop predictive models and analytics to prioritize vulnerabilities by risk and business impact; analyze large-scale security telemetry; build ML/statistical models to remove scanning noise and false positives; and create unified data delivery structures and dashboards to enable data-driven security governance.
Top Skills:
PythonPyTorchRSQLTensorFlow
What you need to know about the Austin Tech Scene
Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
Key Facts About Austin Tech
- Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
- Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
- Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
- Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center
