Staff Data Scientist - Cyber Risk Analytics & ML

BitSight Technologies; Boston (MA); On-site; USD 125,000 - 189,000; Full time

Benefits offered by this job

Health insurance

Parental leave

Flexible time off

401(k)

Life and disability insurance

Tuition reimbursement

Job summary

Bitsight is seeking a Staff Data Scientist to develop predictive cyber risk models and improve its Security Ratings and Risk Vector methodologies. You will collaborate with Engineering, Product, Marketing, and Customer Success to deliver robust, scalable data-driven solutions.

The role requires MS degree (PhD preferred) in a quantitative field, 1+ year staff experience, and strong skills in Python/R, SQL, AWS, and ML. Hybrid work and equity are offered.

Qualifications

• MS degree required; PhD preferred in quantitative field.
• 1+ year staff-level experience in industry.
• Experience modeling risk for rare events is desirable.
• Proficiency with Git, Python/R, SQL; big data stack; ML, modeling, validation; data viz and reporting; AWS.

Responsibilities

• Research and implement statistical and ML methods for cybersecurity risk assessment.
• Maintain and enhance Security Ratings and Risk Vector scoring methodologies.
• Explore new data sources to improve models and capabilities.
• Apply AI/ML techniques to solve complex cybersecurity problems.
• Develop scalable, well-documented data science pipelines and models.
• Monitor model performance and investigate anomalies.
• Communicate technical concepts and contribute to docs.
• Anticipate product-level design issues and address them proactively.

Skills

Git

Python/R

SQL

Spark/Hadoop

Applied ML

Predictive modeling

Statistical analysis

Data visualization

AWS

AI-assisted tools

Education

MS degree

PhD preferred

Tools

Spark

Hadoop

Claude Code

Cursor

GitHub Copilot

Job description

Bitsight is seeking a Staff Data Scientist to develop predictive cyber risk models and improve its Security Ratings and Risk Vector methodologies. You will collaborate with Engineering, Product, Marketing, and Customer Success to deliver robust, scalable data-driven solutions.

The role requires MS degree (PhD preferred) in a quantitative field, 1+ year staff experience, and strong skills in Python/R, SQL, AWS, and ML. Hybrid work and equity are offered.