below marketmost similar roles pay hereabove market
This role pays more than
88%
of similar roles. Most pay
$131,500–$199,650
— the blue band above.
At the midpoint, this role pays about
$216k
versus about
$166k
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 Lead Data Scientist – Cyber Security Operations Center joins the Data Science & Analytics team to protect customers by identifying malicious activity on the Salesforce platform. This technical leader will establish the vision for AI-driven detection, architecting end-to-end frameworks and overseeing proofs-of-concept for novel threat models. Day-to-day responsibilities include building agentic monitoring systems, automated threat correlation, and continuous model feedback loops while mentoring junior staff and collaborating with threat intelligence experts. The role requires expertise in applied statistics, deep learning, sequence modeling, and NLP/LLMs. Candidates must demonstrate proficiency in Python, Java, or Scala, alongside big data frameworks like Spark, PySpark, and Flink. The work focuses on solving complex security challenges through behavior-based detection, signal correlation, and analyzing security logs like SIEM and EDR data.
Define the technical vision, methodology, and roadmap for AI-driven detection capabilities within the CSOC.
Architect and oversee the execution of proofs-of-concept for novel threat detection models.
Transition threat detection models into high-throughput, scalable production software.
Lead partnerships with incident response and threat intelligence teams to identify detection gaps.
Design and maintain enterprise AI-driven capabilities, including agentic monitoring and automated threat correlation.
Mentor data scientists and establish best practices for code quality, model governance, and ML pipeline reliability.
Translate complex machine learning models and security signals into actionable insights for executive leadership.
What we're looking for
8+ years of industry experience in applied data science, machine learning, or AI engineering.
6+ years of experience with a relevant Master’s or Ph.D. degree.
3+ years in a technical leadership capacity owning project lifecycles from ideation to production.
Deep expertise in applied statistics, probability, and advanced machine learning techniques including deep learning, sequence modeling, anomaly detection, and NLP/LLMs.
Demonstrated experience architecting and deploying ML pipelines and models over large-scale datasets.
Production-level programming skills in Python, Java, or Scala with fluency in big data frameworks like Spark, PySpark, or Flink.
Proven track record of guiding cross-functional technical decisions and mentoring engineering and data science team members.
Domain expertise in Cybersecurity, specifically in threat propagation, signal correlation, and behavioral threat modeling (preferred).