Senior Data Scientist, Applied ML

This is a fully remote position, open to applicants in Texas.

📋 Description

• Design, develop, train, and implement models for cybersecurity applications, including incident detection and response, fraud intelligence, and risk assessment.

• Create models utilizing both structured and unstructured data for threat detection, alerting, entity resolution, risk scoring, and natural language tagging and classification.

• Construct preprocessing and feature engineering pipelines that support these models.

• Take ownership of model monitoring and evaluation, designing feedback loops to enhance accuracy and effectiveness.

• Prototype innovative approaches and transition prototypes to production-grade reliability.

• Manage data validation, transformation, and pipeline integrity throughout the research-to-production transition.

• Collaborate with software and data engineers to integrate models into cloud-native platforms such as AWS.

• Work alongside product managers and domain experts to establish success criteria and prototype minimum viable products (MVPs).

• Access, comprehend, transform, and validate a variety of data sources in conjunction with data engineering teams.

• Contribute to system design and architectural decisions.

• Articulate model design decisions, trade-offs, and results to both technical and non-technical stakeholders.

• Maintain comprehensive documentation for models, pipelines, and evaluation methods.

• Engage in model and compliance reviews and participate in customer-facing discussions as required.

⛳️ Requirements

• Over 4 years of experience in developing and deploying models in production with direct, hands-on responsibility for the data lifecycle surrounding them.

• Solid foundation in applied mathematics, including linear algebra, optimization, statistics, and machine learning.

• Proven experience utilizing Natural Language Processing (NLP) techniques for text classification, tagging, or entity extraction.

• Proficiency in Python, along with frameworks such as PyTorch, TensorFlow, scikit-learn, and XGBoost.

• Demonstrated experience in building or maintaining data/feature pipelines using tools like Airflow, Spark, or Pandas as part of modeling efforts.

• Familiarity with model versioning and monitoring in production environments, such as MLflow or DVC.

• Practical experience in deploying models within cloud environments or as containerized services.

• Strong communication abilities and the capacity to convert complex challenges into actionable solutions.

• Please note that SpyCloud is not currently sponsoring visas.

🏝️ Benefits

• Flexible and remote-friendly work arrangements.

• Competitive salary package.

• 401(k) plan with Employer Contributions.

• Health, Vision, and Dental Insurance coverage.

• Health Savings Account (HSA) available with Employer Contribution.

• Employer-paid Life, Short-term, and Long-term Disability Insurance.

• Generous Paid Time Off (PTO) Plan, along with 16 paid holidays each year.

• Retirement Savings Plan with Employer Contributions.

• Employer-provided Private Health Insurance and Healthcare Cashplan.

• Employer-paid Life Insurance and Income Replacement benefits.

• Generous Holiday Plan featuring 14 paid holidays each year.