Sr. Data Scientist

About This Opportunity

We are representing a confidential cybersecurity organization in their search for a Senior Data Scientist to join an elite team focused on AI-driven security operations. This role will design, build, and deploy advanced AI systems that analyze and prioritize millions of security events per second, enabling rapid threat identification and response. You will develop intelligent models for anomaly detection, event classification, ranking, correlation, and automated security reasoning while taking ownership of complex technical challenges and driving innovation across the AI stack.

Responsibilities

• Lead the architecture and technical strategy for large-scale retrieval, ranking, vector search, RAG, and anomaly detection systems operating at enterprise scale
• Drive innovation across LLMs, AI-powered discovery, personalization, and autonomous AI workflows
• Own end-to-end AI/ML architecture, including data pipelines, feature engineering, model development, deployment, monitoring, evaluation, and continuous improvement
• Establish scalable architecture patterns, engineering standards, experimentation frameworks, and operational best practices across multiple teams
• Define evaluation methodologies, experimentation strategies, and success metrics to assess product, model, and business impact
• Partner closely with Product, Engineering, Security, Infrastructure, and Operations teams to identify high-value opportunities and deliver scalable AI solutions
• Lead highly ambiguous, multi-quarter initiatives spanning Product, Engineering, Data Science, and other stakeholders
• Influence organization-wide technical strategy, investment priorities, and long-term AI roadmap decisions
• Communicate technical trade-offs, recommendations, and results clearly to both technical and executive audiences
• Mentor junior scientists while fostering a culture of technical excellence and innovation

What We're Looking For

• 8+ years of experience building and scaling large-scale AI/ML, search, retrieval, and ranking systems 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 understanding of retrieval and ranking trade-offs, experimentation methodologies, model evaluation, and operational excellence
• 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
• Strong programming skills in Go, Python, SQL, and modern machine learning ecosystems
• Experience designing and deploying end-to-end ML solutions, including data acquisition, feature engineering, model development, evaluation, deployment, and monitoring
• Strong knowledge of experimentation frameworks, online evaluation, A/B testing, causal inference, and model validation methodologies
• 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
• Proven experience utilizing AI technologies to enhance decision-making, streamline workflows and processes, improve efficiency and drive business outcomes

Core 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, Vector Search, Hybrid Search, Embeddings, Retrieval Systems, Knowledge Graphs, Kubernetes, Distributed Systems, Model Serving, Feature Stores, ML Pipelines, Threat Detection, Security Analytics, UEBA, Detection Engineering

Bonus Qualifications: Published research, patents, open-source contributions, or recognized thought leadership in AI, machine learning, search, retrieval, or cybersecurity; Experience building large-scale search, recommendation, retrieval, or agentic AI systems serving enterprise or consumer products; Experience leading technical strategy for AI platforms, ML infrastructure, or AI-native product initiatives; Demonstrated success driving zero-to-one innovation and scaling solutions to enterprise-wide adoption

How We Work With You

When you apply through Get A Job.ai, our talent team conducts an initial screening to understand your background and match you with the right opportunity. We then present qualified candidates to our client for their review and interview process. Please apply directly through our platform and do not contact the client independently, as all communication is coordinated through our recruiting team to ensure the best experience for everyone involved.

Pay

Pay information will be discussed during the screening process based on experience, location, and client budget.

Equal Opportunity: Get A Job.ai is committed to inclusive hiring practices and equal employment opportunity. We welcome applications from all qualified candidates regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected characteristic.