Description
The Data Science & Analytics team in the Salesforce Cyber Security Operations Center seeks an experienced, visionary, and driven Lead Data Scientist to help protect our customers and identify malicious activity on our platforms.
As a technical leader on a growing and highly visible team, you will establish technical direction, architect end-to-end detection frameworks, and partner with executive, threat, product, and engineering teams to deliver autonomous defenses that operate at cloud scale,evolving through agentic-based monitoring, testing, and continuous improvement.
Responsibilities
- Strategic & Technical Leadership: Define the technical vision, methodology, and roadmap for data science and AI-driven detection capabilities within the CSOC.
- Architecture & Delivery: Architect, build, and oversee the execution of proofs-of-concept for novel threat detection models, ensuring seamless transition into high-throughput, scalable production software.
- Cross-Functional Influence: Lead partnerships with incident response, threat intelligence, detection engineering, and product security teams to identify detection gaps and model evolving adversary behavior.
- AI & Agentic Systems Ownership: Champion, design, and maintain enterprise AI-driven capabilities, including agentic monitoring systems, automated threat correlation, and continuous model feedback loops.
- Mentorship & Technical Governance: Mentor senior and junior data scientists, establish best practices for code quality, model governance, testing, and ML pipeline reliability.
- Executive Communication: Translate complex machine learning models and security signals into actionable insights and strategic proposals for security leadership, engineers, and non-technical stakeholders.
Required Experience & Skills
- 8+ years of industry experience in applied data science, machine learning, or AI engineering (or 6+ years with a relevant Master’s or Ph.D.).
- 3+ years in a technical leadership capacity (e.g., Lead Data Scientist, Tech Lead, or Principal Individual Contributor) owning project lifecycles from ideation to production.
- Deep expertise in applied statistics, probability, and advanced machine learning techniques (deep learning, sequence modeling, anomaly detection, NLP/LLMs).
- Demonstrated experience architecting and deploying ML pipelines and models over large-scale datasets (multi-terabyte or petabyte scale).
- Production-level programming skills in Python, Java, or Scala, along with fluency in big data frameworks (e.g., Spark, PySpark, Flink) and modern MLOps ecosystems.
- Proven track record of guiding cross-functional technical decisions and mentoring engineering and data science team members.
- Exceptional strategic communication skills, with the ability to influence technical roadmaps and articulate complex concepts to leadership.
Benefits
- Time off programs
- Medical, dental, vision
- Mental health support
- Paid parental leave
- Life and disability insurance
- 401(k)
- Employee stock purchasing program