Sr. Data Scientist (Hybrid)

Job Summary

Required Qualifications

• 8+ years of experience building and scaling large-scale AI/ML, search, retrieval, ranking in the cybersecurity space
• MS, PhD, or equivalent industry experience in Computer Science, Statistics, Physics, or a related quantitative discipline
• Deep expertise in semantic retrieval, vector search, ranking systems, recommendation systems, NLP/LLMs, RAG architectures, and agentic AI systems
• Strong programming skills in Go, Python, SQL, and modern machine learning ecosystems
• Experience operating large-scale production systems with demanding latency, scalability, reliability, and cost requirements
• Proven track record of delivering measurable business impact through AI and machine learning innovation
• Experience leading cross-functional initiatives across multiple organizations and stakeholder groups
• Ability to influence executive stakeholders and drive strategic technical decisions across large organizations
• Exceptional communication, leadership, strategic thinking, and mentoring skills
• Experience designing and deploying end-to-end ML solutions, including data acquisition, feature engineering, model development, evaluation, deployment, and monitoring
• Proficiency in Anomaly Detection, MITRE entities, Detection Engineering, Triage and Investigation
• Experience with modern AI infrastructure, large-scale data processing, distributed systems, and production ML platforms
• Ability to communicate data-driven insights, uncertainty, assumptions, and trade-offs to technical and non-technical audiences
• Technologies: Python, Go, SQL, Spark, Kafka, S3, Iceberg, Parquet Machine Learning, Deep/Reinforcement Learning, Time-Series Modeling, Anomaly Detection, Recommendation Systems, Ranking Systems LLMs, RAG, Agentic AI, Multi-Agent Systems, AI Evaluation Vector Search, Hybrid Search, Embeddings, Retrieval Systems, Knowledge Graphs, Ranking & Relevance Optimization Kubernetes, Distributed Systems, Model Serving, Feature Stores, ML Pipelines, Experimentation Platforms, Model Monitoring Threat Detection, Security Analytics, UEBA, Detection Engineering, AI-Powered SOC Workflows
• Bonus Points":"Published research, patents, open-source contributions, or recognized thought leadership in AI, machine learning, search, retrieval, or cybersecurity"],
• restrictions":[],
• summary":"Senior Data Scientist to design, build, and deploy AI systems that analyze and prioritize millions of security events per second, develop intelligent models for anomaly detection, event classification, ranking, and automated security reasoning; own end-to-end AI/ML architecture, data pipelines, feature engineering, model development, deployment, monitoring, and experimentation; mentor junior scientists and collaborate with Product, Engineering, Security, Infrastructure, and Operations teams; role based in Sunnyvale, CA with 2 days on-site weekly; requires 8+ years in AI/ML, strong Go/Python/SQL skills, and experience delivering measurable business impact in cybersecurity."
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