[Hiring] Data Scientist / Software Engineer @Binary Defense

Role Description

Binary Defense is seeking a talented Data Scientist / Software Engineer to join our team in a dual-discipline role bridging applied data science and production software engineering. This is not a research-only or notebook-only position — you will own the full lifecycle of data-driven capabilities, from hypothesis to deployed service running in our production environment supporting MDR operations and the NightBeacon product suite.

• Design, build, and ship production-grade data and ML systems that operate against large-scale cybersecurity telemetry, including endpoint, network, identity, and cloud-derived signals.
• Apply analytical, statistical, and machine learning techniques to collect, analyze, and interpret large cybersecurity data sets, and translate findings into deployable software.
• Develop, test, and maintain backend services, APIs, and data pipelines that integrate ML models and analytics into Binary Defense products and SOC tooling.
• Collaborate closely with software engineering, product, detection engineering, and security engineering teams to embed algorithms and analytics directly into our platforms.
• Own code quality across the stack — write clean, well-tested, reviewed code; participate in design reviews; and contribute to architectural decisions affecting data and ML systems.
• Operationalize models with appropriate monitoring, versioning, retraining, and rollback strategies (MLOps).
• Contribute to product, services, and detection engineering roadmap by identifying where data science and engineering investment will measurably improve outcomes for analysts and clients.
• Develop data-driven solutions that ship — not prototypes that stall.

Qualifications

• Master's or PhD in Computer Science, Machine Learning, Data Science, Statistics, or equivalent experience.
• At least 3 years of experience as a data scientist, ML engineer, or applied research engineer, ideally supporting cybersecurity applications.
• Working knowledge of linear algebra, statistics, probability, and the mathematics underlying modern ML.
• Strong understanding of statistical modeling supervised and unsupervised learning, and the tradeoffs between classical ML and deep learning approaches.
• Hands-on experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Experience with big data technologies (Spark, Hadoop ecosystem, or modern equivalents) and NoSQL data stores.
• Experience with data visualization and analyst-facing tooling (Tableau, Power BI, D3.js, or similar).
• At least 3 years of experience writing production software, with code shipped to real users in a team setting.
• Strong proficiency in Python, plus working competence in at least one additional production language (Go, Rust, C#/.NET, Java, or TypeScript).
• Solid foundations in software design: data structures, algorithms, OOP and functional patterns, API design, and system design for performance and scale.
• Experience designing and building REST or gRPC APIs and the services behind them.
• Strong with relational and NoSQL database design, query optimization, and schema evolution.
• Proficient with Git, modern code review workflows, and writing unit and integration tests.
• Comfortable with CI/CD pipelines and shipping behind feature flags or staged rollouts.
• Experience with containerization (Docker) and at least one orchestration or deployment platform (Kubernetes, ECS, or equivalent).
• Familiarity with cloud platforms — AWS, Azure, or GCP — including their managed data, compute, and ML services.
• Excellent written and verbal communication; able to defend technical decisions and write documentation that engineers and analysts will use.

Requirements

• Direct experience applying data science to security problems: detection engineering, threat intelligence enrichment, behavioral analytics, malware classification, alert triage, or adversary attribution.
• Experience with managed ML services such as Amazon SageMaker, Vertex AI, or Azure ML.
• Familiarity with LLM-based systems, including retrieval-augmented generation, agentic workflows, evaluation frameworks, and prompt and model lifecycle management.
• Experience operating in an Agile or continuous-delivery environment.
• Knowledge of data privacy and security regulations such as GDPR, CCPA, or HIPAA, and experience handling sensitive customer data accordingly.
• Familiarity with DevOps and SRE practices, including infrastructure-as-code (Terraform), observability (metrics, logs, traces), and incident response.
• Background or prior role in threat intelligence, security research, security engineering, or SOC analysis.
• Strong work ethic, intellectual honesty, and creative problem-solving — comfortable working through ambiguity and shipping under real deadlines.

Benefits

• Competitive medical, dental and vision coverage for employees and dependents.
• 401k match which vests every payroll.
• Flexible and remote friendly work environment.
• Training opportunities to expand your skill set.