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Senior Director, Security Analytics

Salesforce

WAJobPosted 3w agoStill listed 1 day ago

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At a glance

Compensation
No compensation found
Location
WA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Senior Director, Security Analytics owns the strategy, development, and operation of data science and machine learning capabilities embedded in Salesforce’s customer-facing security products. The role leads a specialized team and partners with product and engineering groups to protect identities, networks, AI products, and customers from emerging threats. It drives analytics and automated containment across large-scale, multi-tenant SaaS environments.

Skills & qualifications

RequiredNice to have

Skills

Data ScienceMachine LearningThreat DetectionStatistical ModelingSoftware as a Service (SaaS)Security Data ScienceMachine Learning EngineeringSecurity AnalyticsProduction ML ModelsMulti-Tenant SaaSImbalanced DatasetsCold-Start Tenant ModelsAdversarial ML EvasionModel ExplainabilityAutomated Threat ContainmentCross-Functional LeadershipAI SecurityWritten CommunicationVerbal CommunicationReal-Time Data StreamingSparkFlinkKafkaDatabricksPyTorchTensorFlowScikit-Learn

Qualifications

10+ Years Experience

Benefits

Paid Time Off
Medical Insurance
Dental Insurance
Vision Insurance
Parental Leave
401(k) Match

Full job description

Description Location: Bellevue, WA or McLean, VA

The Experience

As a Senior Director, Security Analytics, you own the strategy, development, and operation of data science and machine learning (ML) capabilities built directly into our customer-facing security products. High-scale software as a service (SaaS) environments require real-time, automated threat detection and containment across millions of active users and hundreds of thousands of customer organizations. You lead a specialized team of security data scientists, ML engineers, and detection engineers, engaging cross-functional product and engineering teams to safeguard customer identities, network perimeters, AI products, and counter emerging AI attacks at scale.

What You’ll Actually Be Doing

  • Own the customer-facing security analytics roadmap end to end, driving strategy for AI product defense, identity, network and application programming interface (API) threat prevention, and adversarial AI threat containment.
  • Build native customer-facing safeguards against AI-specific attacks, including prompt injection, model inversion, data poisoning, and unauthorized large language model (LLM) data exfiltration.
  • Design analytics that use automated containment mechanisms, such as adaptive step-up authentication, API rate-limiting, and session revocation, to neutralize active threats instantly without disrupting customer operations.
  • Partner with Product Management, user experience (UX), and executive stakeholders to translate complex statistical outputs into clear security insights and trust dashboards for customer administrators, while reporting system performance, model metrics, drift analysis, and threat containment service level agreements (SLAs) to leadership.

You’re Our Person If...

  • You have 10+ years of experience in security data science, machine learning engineering, or building customer-facing security analytics products at scale, with 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, with a proven record of detecting and stopping attackers at cloud-level scale.
  • You’ve worked directly with Product, Engineering, and Incident Response teams to drive automated threat containment features to completion, and can align cross-functional senior leadership around complex security data science initiatives.
  • You communicate complex statistical modeling and AI security concepts clearly to executive stakeholders and customers, with excellent written and verbal communication skills.

Even Better If...

  • You have familiarity with real-time big data streaming infrastructure (Spark, Flink, Kafka, Databricks).
  • You have experience with modern ML frameworks (PyTorch, TensorFlow, Scikit-Learn).

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.

How this job compares

Set against the 2,105 open Data Science jobs on Olive Jobs, counted November 6, 2026.

Pay
  • This postingNot listed
  • Washington median$143–235K/yr69 salary ranges
  • US median$37–51/hr130 hourly ranges
Openings
Olive Jobs lists 85 open Data Science jobs in Washington and 2,105 across the US. 5% of them nationwide are listed as remote or flexible.
Hiring the most in Washington
Experience
This posting asks for at least 10 years of experience — more than three in four Data Science postings that state a minimum ask for (median 6 years, across 1,682 postings).
Education
919 of the 2,105 open Data Science jobs (44%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 6, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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