The opportunity:Methodology data scientists at Bitsight are responsible for researching, developing, and implementing statistical and machine learning methodologies to assess cybersecurity risks and help organizations better understand and manage their cyber exposure. As a Staff Data Scientist, you will play a key role in developing predictive cyber risk models, maintaining and enhancing Bitsight's Security Ratings and Risk Vector methodologies, and translating complex analytical solutions into scalable production systems.
You will collaborate closely with Engineering, Product Management, Marketing, Customer Success and other teams to develop robust, explainable, and data-driven solutions to complex cybersecurity problems.The ideal candidate has a strong background in statistics, machine learning with an interest in cybersecurity, risk assessment, and applying emerging AI technologies to solve real-world problems.
Job Responsibilities:- Research, develop, validate, and implement statistical and machine learning methodologies for cybersecurity risk assessment and prediction.
- Maintain and enhance Bitsight's Security Ratings and Risk Vector scoring methodologies, ensuring accuracy, robustness, and explainability.
- Explore new cybersecurity, threat intelligence, and firmographic data sources to improve existing models and develop new capabilities.
- Explore and apply emerging AI/ML techniques and tools to solve complex cybersecurity problems.
- Develop and maintain scalable, reliable, well-documented, and tested code for data science models, scoring algorithms, and data processing pipelines.
- Monitor model performance, investigate anomalies, and identify opportunities for improvements.
- Communicate complex technical concepts and contribute to internal and customer-facing documentation.
- Anticipate technical issues at the product level and make design decisions to avoid them.
Job Requirements:- Education: MS required. PhD preferred in Statistics, Applied Mathematics, Computer Science, Physics, Engineering, or other Quantitative Science
- Years of Experience: minimum 1 year equivalent industry experience at the staff level
- Prior experience with the modeling of risk for rare events is desired.
- Certification/Specialized Skills: Git, Python/R, SQL; software SDLC and package/library development; shell/bash/command line scripting; big data stack (Spark/Hadoop); applied machine learning, predictive modeling, statistical analysis, and model validation; data visualization and reporting tools; AWS; ability to manipulate, clean, and combine large, complex disparate data sources; ability to read, learn, and evangelize algorithms and statistical methodologies from peer-reviewed literature; hands-on experience leveraging AI-assisted development tools (e.g., Claude Code, Cursor, GitHub Copilot) to improve coding, analysis, testing, and development productivity.
The anticipated hiring base salary range for this position is 125,000.00 - 189,000.00 USD Annual for US-based employees. This range reflects the minimum and maximum target for new hire salaries for the position across all US locations, is based on a full-time work schedule, and is Bitsight's good faith estimate as of the date of this posting. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
In addition to base salary, this role is eligible for participation in a bonus or commission plan and an equity grant. Bitsight also offers a competitive benefits package, including but not but limited to medical, dental, and vision insurance; paid parental leave; flexible time off; a 401(k) plan with employee and company contribution opportunities; life and disability insurance; and tuition reimbursement.
