• Data Science
• Machine Learning
• AI
• Kubernetes
• Anomaly Detection
• Predictive Modeling
• Data Pipelines
• Platform Observability
• Telemetry
• Python
• Data Engineering
• SRE
• Distributed Systems
• Capacity Planning
• Analytics Dashboards
• Feature Engineering
• Data Governance
• NLP
• Deep Learning
• Automation

As a Lead Data Scientist on the Falcon Kubernetes Platform (FKP) team, you will drive AI and data intelligence initiatives that improve platform resilience, availability, capacity planning, and operational efficiency across Salesforce's multi-substrate container platform powering Core CRM and platform services.

You will build AI-driven systems to automate alert triage, anomaly detection, failure prediction, routing recommendations, resource optimization, and remediation workflows. Working closely with SREs and platform engineers, you will translate operational pain points into scalable AI and analytics solutions.

Key responsibilities include developing data pipelines, feature repositories, and telemetry ingestion frameworks for large-scale platform observability, building analytics dashboards for insights into cluster health, node behavior, workloads, SLA adherence, and failure modes. You will drive data-informed decisioning for nodepool planning, release readiness, capacity scaling, and multi-region deployments.

You will design AI-assisted runbooks, knowledge extraction systems, and automation logic embedded into platform tooling. The role involves contributing to architectural discussions on data flows, analytics infrastructure, and AI integration strategy, establishing standards for data quality and governance, and mentoring data engineers and data scientists.

The ideal candidate is passionate about improving large-scale distributed platforms through data, automation, and AI-driven intelligence, with experience working with high-volume operational telemetry including logs, events, metrics, and traces.