Note: The job is a remote job and is open to candidates in USA. LS Solutions is seeking a combined Data Scientist and Software Engineer responsible for developing, deploying, and maintaining data-driven and machine learning systems supporting cybersecurity operations and products. The role involves designing and implementing production-grade systems, collaborating with teams, and ensuring high-quality code while operationalizing models.
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
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
- 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
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