Data Scientist, Software Engineer

🕒 May 15

🤠 Texas – Remote

🤠 Texas – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

Apply Now

Find Similar Remote Jobs

Receive Emails For Remote Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

Binary Defense

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2014

🔐 Security

🔒 Cybersecurity

☁️ SaaS

💰 Private Equity Round on 2022-11

Security • Cybersecurity • SaaS

Binary Defense is a cybersecurity firm that provides a range of security services designed to protect businesses from digital threats. The company operates as an extension of client teams, offering managed detection and response, co-managed SIEM, threat hunting, and digital risk protection services around the clock. With a focus on increasing security visibility and reducing complexity, Binary Defense uses a combination of human expertise and technology to offer comprehensive threat detection and response. Their services also include phishing response and incident response, all delivered through a 24/7 security operations center. By integrating advanced threat intelligence and tactical remediation strategies, Binary Defense aims to stay ahead of emerging cyber threats, ensuring the safety of client digital assets.

📋 Description

• Design, build, and ship production-grade data and ML systems • Apply analytical, statistical, and machine learning techniques to collect, analyze, and interpret large cybersecurity data sets • Develop, test, and maintain backend services, APIs, and data pipelines • Collaborate closely with software engineering, product, detection engineering, and security engineering teams • Own code quality across the stack • 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

🎯 Requirements

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

🏖️ 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