Lead Data Scientist – Cyber Security Operations Center

Salesforce•McLean, VA

13d•$172,500 - $285,800

About The Position

The Salesforce Cyber Security Operations Center’s Data Science & Analytics team seeks an experienced, visionary Lead Data Scientist to help protect customers and identify malicious activity on Salesforce platforms. The team develops and scales capabilities using AI, machine learning, and contemporary data techniques to advance behavior- and signature-based detection. As a technical leader on a growing, 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 at cloud scale. The work includes evolving agentic-based monitoring, testing, and continuous improvement. You will research and architect advanced techniques in generative AI, agentic workflows, data mining, and machine learning, taking innovations from concept through production deployment.

Requirements

At least 8 years of industry experience in applied data science, machine learning, or AI engineering, or at least 6 years with a relevant Master’s or Ph.D.
At least 3 years in a technical leadership capacity, owning project lifecycles from ideation through 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, multi-terabyte or petabyte-scale datasets.
Production-level programming skills in Python, Java, or Scala, and fluency with big data frameworks such as Spark, PySpark, or Flink and modern MLOps ecosystems.
A track record of guiding cross-functional technical decisions and mentoring engineering and data science team members.
Strategic communication skills and the ability to influence technical roadmaps and explain complex concepts to leadership.

Nice To Haves

Cybersecurity domain expertise, particularly in threat propagation, signal correlation, security log analysis (SIEM, EDR, network flows), and behavioral threat modeling.
Hands-on experience building and deploying agentic AI systems, automated reasoning, or generative AI workflows in high-consequence operational environments.
Experience in other high-throughput, low-latency fields involving pattern recognition and behavioral analysis, such as quantitative finance, high-frequency trading, genomics, or fraud detection.

Responsibilities

Define the technical vision, methodology, and roadmap for data science and AI-driven detection capabilities within the CSOC.
Architect, build, and oversee proofs of concept for novel threat detection models, ensuring their transition into high-throughput, scalable production software.
Lead partnerships with incident response, threat intelligence, detection engineering, and product security teams to identify detection gaps and model evolving adversary behavior.
Design, champion, and maintain enterprise AI-driven capabilities, including agentic monitoring systems, automated threat correlation, and continuous model feedback loops.
Mentor data scientists and establish best practices for code quality, model governance, testing, and ML pipeline reliability.
Translate machine learning models and security signals into actionable insights and strategic proposals for security leadership, engineers, and non-technical stakeholders.