Lead Data Scientist - Cyber Security Operations Center

Leadout Capital; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

Leadout Capital seeks a Lead Data Scientist to shape AI-driven security analytics for its cybersecurity program. You will define the data science strategy, architect scalable detection models, and partner with threat intelligence and engineering teams to deploy production-grade solutions.

The role demands deep ML expertise, leadership experience, and the ability to communicate complex insights to executives and engineers alike. Expect a high-impact, cloud-scale environment.

Qualifications

• 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 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).
• 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 (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.

Responsibilities

• Define the technical vision, methodology, and roadmap for data science and AI-driven detection capabilities within CSOC.
• Architect, build, and oversee the execution of proofs-of-concept for novel threat detection models, ensuring seamless 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.
• Champion, design, and maintain enterprise AI-driven capabilities, including agentic monitoring systems, automated threat correlation, and continuous model feedback loops.
• Mentor senior and junior data scientists, establish best practices for code quality, model governance, testing, and ML pipeline reliability.
• Translate complex machine learning models and security signals into actionable insights and strategic proposals for security leadership, engineers, and non-technical stakeholders.

Skills

Technical Leader & Strategist

Innovator & Architect

Force Multiplier

Executive Communication

Tools

Python/Java/Scala

Spark PySpark Flink

Job description

Lead Data Scientist – Cyber Security Operations Center

The Team

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. We explore, invent, build, and scale advanced capabilities to secure the Salesforce platform. We leverage AI, machine learning, and contemporary data techniques to advance behavior- and signature-based detection mechanisms.

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.

About You

• Technical Leader & Strategist: You possess a deep passion for AI and data, combined with a proven track record of converting complex security challenges into scalable data science initiatives. You bridge rigorous statistical theory with high-impact business and operational security outcomes.
• Innovator & Architect: You thrive on researching, evaluating, and architecting cutting-edge techniques in generative AI, agentic workflows, data mining, and machine learning, driving innovations from initial concept through production deployment.
• Force Multiplier: You are a natural collaborator and mentor who elevates those around you. You partner fluently with threat intelligence experts to decipher emerging attack vectors and collaborate with principal software engineers to set the architectural standards for production security algorithms.
• You wanna stop bad guys: You enjoy creating chaos for cyber attackers and want to disrupt their operations.

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.

Preferred Skills

• Domain expertise in Cybersecurity, specifically 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 domains involving pattern recognition and behavioral analysis (e.g., quantitative finance, high-frequency trading, genomics, or fraud detection).