Data Scientist jobs in United States

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Make an Impact in Cybersecurity as a Network Security Data Scientist

Are you passionate about making the digital world safer? This is an opportunity to join a cutting-edge team that's redefining how organisations detect and respond to cyber threats by leveraging the network itself as a source of truth. Attackers can bypass endpoint defences and firewalls—but they can’t avoid leaving traces in the network traffic.

Built upon powerful open-source technologies like Zeek, Suricata, and YARA, this organisation is transforming data from physical, virtual, and cloud networks into high-value security insights. Their customers—spanning industries from enterprise to government—rely on these insights for rapid incident response and proactive threat hunting.

About the Role:

This position sits within a specialised R&D team that blends data science, machine learning, and deep security expertise. As a Network Security Data Scientist, you will collaborate with ML engineers and security analysts to create state-of-the-art detection models, build agentic applications using LLMs, and develop visibility solutions that no other product in the market currently delivers.

You’ll be directly involved in shaping the structure and content of the data that drives advanced analytics, helping to power the next generation of security solutions.

Key Responsibilities:

• Drive AI/ML projects from exploration to production deployment.
• Apply supervised and unsupervised techniques to detect diverse attacker behaviours under real-world constraints.
• Build and refine LLM-powered solutions using frameworks such as Langchain, LlamaIndex, Chroma, and LangGraph, customising them with RAG and fine-tuning for cybersecurity use cases.
• Design behavioural detection models using network traffic data (e.g. Zeek logs), optimised for low false positives.
• Collaborate on scalable ML pipelines with engineers and network security experts.
• Evaluate models using large-scale, real-world datasets.
• Operate in an Agile development environment and participate in cross-functional technical discussions.
• Author technical documentation to support both internal teams and the broader cybersecurity community.

Minimum Qualifications:

• Degree in Computer Science or a related field (or equivalent experience).
• 3+ years of experience in data science or building LLM applications, especially in the cybersecurity domain.
• Strong practical experience in Python and tools like Scikit-Learn, TensorFlow, PyTorch, Keras, Pandas, Polars, Spark, and DuckDB.
• Demonstrated experience applying LLMs to cybersecurity or other high-complexity, domain-specific problems.
• Understanding of network and cloud security concepts.
• Excellent communication skills and team collaboration abilities.
• A strong commitment to learning, curiosity, and a low-ego, results-oriented work style.

Preferred Qualifications:

• Knowledge of the threat detection lifecycle and the broader cybersecurity product landscape.
• Experience deploying and fine-tuning Small Language Models (SLMs) locally.
• Familiarity with cloud platforms like AWS (EC2, S3, CloudWatch) and services such as Databricks.
• Hands-on experience with Docker, Kubernetes, and container orchestration.
• Experience building and maintaining data pipelines, especially using DuckDB.
• Familiarity with feature stores, ML platforms like Kubeflow, BentoML, Cortex, and experiment tracking tools.

About the Organisation:

This company is among the fastest-growing players in the network detection and response space, backed by top-tier investors and trusted by global enterprises and research institutions. They are pioneers in AI-assisted security operations, cloud-native threat detection, and SaaS-based solutions. With a global, remote-friendly team and a strong commitment to diversity, inclusion, and innovation, they offer a dynamic environment where passionate professionals can do their best work.

• Seniority level
  Mid-Senior level

• Employment type
  Full-time

• Industries
  Computer and Network Security

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