We9re looking for a Senior Data Scientist, Applied ML to design, build, and deploy models for critical cybersecurity use cases like incident detection and mitigation, fraud intelligence, and risk scoring. You9ll own the full model lifecycle - from data understanding and preparation through prototyping and deployment in production - and work closely with engineering, product, and research teams to turn complex problems into scalable, reliable systems. This role is ideal for someone who thrives in applied, hands-on environments where impact and collaboration matter, and who has genuinely owned data work end-to-end. What You9ll Do: You will develop, train, and deploy models using real-world structured and unstructured data to power critical security features such as threat detection and alerting, entity resolution and risk scoring, and natural language-based tagging and classification. You9ll build the preprocessing and feature engineering pipelines your own models depend on, and you9ll own model monitoring and evaluation, designing feedback loops to continuously improve accuracy and effectiveness. You9ll be equally comfortable prototyping new approaches from scratch and taking existing prototypes - from our R&D team or your own experimentation - to production-grade reliability. This role sits deliberately at the intersection of research and deployment, not on one side of it: you9ll take ownership of data validation, transformation, and pipeline health across the handoff points between research and production, not just within the boundaries of your own models. Working closely with software and data engineers, you9ll help productionize models in modern cloud-native environments like AWS. This role is highly collaborative. You9ll partner with product managers and domain experts to define success criteria, rapidly prototype MVPs to test new features or signals, and work with the data engineering team to access and understand diverse data sources, owning the transformation and validation steps throughout. Your input will also contribute to broader system design and architectural decisions. Strong communication and documentation skills are essential. You will clearly articulate model design choices, tradeoffs, and outcomes to both technical and non-technical stakeholders, maintain thorough documentation for models, pipelines, and evaluation methodologies, and participate in model and compliance reviews and customer-facing discussions as needed. Requirements: 34+ years of experience building and shipping models in production with direct, hands-on ownership of the data lifecycle around them 34Strong background in applied math (linear algebra, optimization, statistics) and machine learning 34Demonstrated experience leveraging Natural Language Processing (NLP) techniques for text classification, tagging, or entity extraction 34Proficiency in Python and key ML libraries: PyTorch, TensorFlow, scikit-learn, XGBoost 34Demonstrated experience building or maintaining data/feature pipelines (e.g., with Airflow, Spark, Pandas) as part of your own modeling work 34Comfort with model versioning and monitoring in production (e.g., MLflow, DVC) 34Working experience deploying models into cloud environments or containerized services 34Strong communication skills and the ability to translate complex problems into actionable solutions Nice to Have: 34Deeper MLOps/DevOps/data engineering exposure: infra-as-code, CI/CD depth, etc. 34Familiarity with cybersecurity datasets or domains: threat intelligence, account takeover, ransomware, etc. 34Exposure to graph analytics, knowledge graphs, or cybersecurity frameworks like MITRE ATT&CK 34Background working with unstructured data (e.g., log files, threat reports, breach datasets) Base Salary Range: $154,000 - $200,000 The salary range reflects the expected base compensation for a fully qualified candidate at this level based on experience, qualifications, and market data at the time of posting. U.S.-Based Benefits + Perks (for Full Time Employees): At SpyCloud, we are committed to working alongside individuals who are equally passionate about preventing cybercrime, regardless of their department or role. Guided by our core values in all business decisions, we prioritize unity in our mission and ensure all SpyCloud employees have the support and benefits they need to stay focused on our goals. In addition to our engaging workspace in South Austin, flexible and remote-friendly work options, and competitive salary package, we offer our employees a comprehensive benefits package that includes: 341(k) with Employer Contribution 34Health, Vision, and Dental Insurance 34Health Savings Account (HSA) available with Employer Contribution 34Employer Paid Life, Short-term, and Long-term Disability Insurance 34Generous PTO Plan and 16 paid holidays per year U.K.-Based Benefits + Perks (for Full Time Employees): 34Retirement Savings Plan with Employer Contribution 34Employer Provided Private Health Insurance and Healthcare Cashplan 34Employer Paid Life Insurance and Income Replacement 34Generous Holiday Plan and 14 paid holidays per year