Data Scientist

Empirical Security is seeking an experienced Data Scientist to join our innovative team focused on building the next generation of cybersecurity vulnerability models. Our unique approach leverages ground-truth telemetry to develop predictive, actionable insights that transform the way organizations identify, prioritize, and remediate vulnerabilities. We build models specific to individual customers, and maintain many of them side by side. This hasn't been done before in cybersecurity. Come change the way security teams make decisions with us.

• Develop robust, predictive vulnerability models using large-scale telemetry data and empirical observations, enabling our customers to connect cybersecurity risks directly to business outcomes.

• Build and refine statistical and machine learning models to predict vulnerability exploitation likelihood, time-to-exploit, and the potential impact of vulnerabilities across various technology stacks.

• Analyze telemetry data and historical vulnerability records to validate and continuously improve model accuracy, identify data quality issues, and recommend actionable remedies.

• Conduct rigorous statistical analysis and validation to assess model performance and quantify uncertainties associated with predictive outputs.

• Collaborate closely with our engineering, product, and security teams to operationalize vulnerability models, ensuring scalability, reliability, and alignment with customer needs.

• Stay abreast of emerging trends and current research in cybersecurity, data science, and machine learning to continually inform and improve modeling techniques.

• Provide technical leadership and mentorship to junior data scientists and analysts, owning model methodologies and data strategy.

• A scientific mindset emphasizing rigor, accuracy, reproducibility, and reliability.

• Strong experience in statistical modeling, predictive analytics, and machine learning, particularly in contexts with sparse, noisy, or incomplete data.

• Proven expertise in Python and experience building scalable data pipelines on cloud environments.

• Proficiency in big data technologies and working in high-performance computing environments.

• Familiarity with software development best practices, including experience with version control systems (Git).

• Deep understanding of the practical applications and limitations of machine learning models in real-world cybersecurity scenarios.

• Excellent communication skills, capable of clearly articulating complex technical concepts and insights to diverse stakeholders and customers.

Don't check off every box in the requirements listed above? Please apply anyway! Studies have shown that marginalized communities - such as women, LGBTQ+ and people of color - are less likely to apply to jobs unless they meet every single qualification. Empirical Security is dedicated to building an inclusive, diverse, equitable, and accessible workplace that fosters a sense of belonging – so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to still consider submitting an application. You may be just the right candidate for this role or another one of our openings!