below marketmost similar roles pay hereabove market
This role pays more than
92%
of similar roles. Most pay
$164,375–$235,487
— the blue band above.
At the midpoint, this role pays about
$292k
versus about
$200k
for comparable roles.
Based on 240 similar postings.
Employer
About Salesforce
Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing
Salesforce currently has
221 open roles
on FindRole.
Listed pay typically runs
$148,500–$260,100
across 125 roles with salary data.
The Senior Director, Security Analytics leads a specialized team of security data scientists, ML engineers, and detection engineers to own the strategy, development, and operation of data science and machine learning capabilities for customer-facing security products. This role involves building native safeguards against AI-specific attacks like prompt injection, model inversion, and data poisoning while designing analytics for automated containment mechanisms such as adaptive step-up authentication and API rate-limiting. The position requires expertise in security-specific data science problems, including imbalanced datasets and adversarial ML evasion. Key technologies and tools include Spark, Flink, Kafka, Databricks, PyTorch, TensorFlow, and Scikit-Learn. The work focuses on real-time, automated threat detection and containment across multi-tenant SaaS environments to protect identities, network perimeters, and AI products from emerging threats.
Own the end-to-end strategy and roadmap for customer-facing security analytics and AI product defense.
Lead a specialized team of security data scientists, ML engineers, and detection engineers.
Build native safeguards against AI-specific attacks like prompt injection, model inversion, and data poisoning.
Design analytics with automated containment mechanisms such as adaptive authentication and API rate-limiting.
Translate complex statistical outputs into clear security insights and trust dashboards for customer administrators.
Report system performance, model metrics, drift analysis, and threat containment SLAs to leadership.
Partner with cross-functional teams to develop automated threat containment features for multi-tenant SaaS environments.
What we're looking for
You have 10+ years of experience in security data science, machine learning engineering, or building customer-facing security analytics products at scale.
You have a track record of shipping production ML models into commercial software platforms across multi-tenant SaaS environments.
You have a strong grasp of security-specific data science/ML problems, including imbalanced datasets, cold-start tenant models, adversarial ML evasion, and model explainability.
You have a proven record of detecting and stopping attackers at cloud-level scale.
You have worked directly with Product, Engineering, and Incident Response teams to drive automated threat containment features to completion.
You can communicate complex statistical modeling and AI security concepts clearly to executive stakeholders and customers.
You have familiarity with real-time big data streaming infrastructure such as Spark, Flink, Kafka, or Databricks (preferred).
You have experience with modern ML frameworks such as PyTorch, TensorFlow, or Scikit-Learn (preferred).
Data Science
Data Engineering
Data Architecture
Business Intelligence
Machine Learning
Artificial Intelligence
Cloud Architecture
Semantic Modeling
Data Quality
Statistical Methods
Data Products
Reporting & Insights
Automation
Data Strategy