Remote Data Scientist / Software Engineer

Role Overview: A combined Data Scientist and Software Engineer responsible for developing, deploying, and maintaining data-driven and machine learning systems supporting cybersecurity operations and products.

Key Responsibilities:

• Design, build, and deploy production-grade data and ML systems analyzing large-scale cybersecurity telemetry.
• Apply statistical and machine learning techniques to interpret cybersecurity data and translate insights into software solutions.
• Develop backend services, APIs, and data pipelines integrating ML models into products and security tools.
• Collaborate with engineering and security teams to embed analytics into platforms.
• Ensure code quality, participate in design reviews, and contribute to architecture decisions.
• Operationalize models with monitoring, versioning, retraining, and rollback strategies (MLOps).
• Identify opportunities where data science can improve detection and security outcomes.
• Develop solutions ready for deployment, avoiding prototypes that remain incomplete.

Qualifications & Skills:

• Master’s or PhD in Computer Science, Data Science, or related fields.
• Minimum of 3 years’ experience in data science, ML engineering, or applied research, preferably in cybersecurity.
• Proficiency in Python and at least one other production language (e.g., Go, Rust, Java).
• Experience with ML frameworks (TensorFlow, PyTorch, scikit-learn) and big data technologies (Spark, Hadoop, NoSQL).
• Strong software engineering foundation: APIs, data structures, algorithms, system design, and testing.
• Knowledge of cloud platforms, containerization, CI/CD, and DevOps practices.
• Excellent communication skills and ability to document technical decisions.

Preferred Skills:

• Experience applying data science to security issues such as threat detection and intelligence.
• Familiarity with managed ML services and LLM-based systems.
• Understanding of security regulations, threat intelligence, and security research.
• Ability to work in Agile environments and handle sensitive data securely.