
Senior Data Scientist
Bugcrowd
full-time
Posted on:
Location Type: Remote
Location: United States
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Salary
💰 $110,720 - $138,400 per year
Job Level
About the role
- Design, develop, and deploy LLM- and RAG-powered applications that enhance analyst and hacker productivity across offensive security use cases.
- Integrate Generative AI models with internal APIs and security datasets to automate and augment workflows.
- Build and fine-tune ML models for vulnerability prediction, triage prioritization, and exploit pattern detection.
- Develop evaluation pipelines and feedback loops to continuously improve AI model performance and explainability.
- Architect and maintain large-scale, high-performance data pipelines to process vulnerability, asset, and activity datasets from multiple sources.
- Build secure data ingestion, transformation, and storage workflows leveraging AWS and modern MLOps practices.
- Develop robust CI/CD pipelines for data and ML model deployment.
- Collaborate with security researchers and engineers to translate offensive security workflows into data-driven automation.
Requirements
- 5+ years of experience in Data Science, Machine Learning Engineering, or Data Engineering.
- Deep experience with Python, AWS services (S3, Lambda, Batch, Glue, Bedrock, Step Functions, Redshift), and ML frameworks (Scikit-Learn, XGBoost, PyTorch, etc.).
- Proven experience building end-to-end ML pipelines — from data ingestion to model deployment and monitoring.
- Strong understanding of LLM technologies, RAG architectures, and API integration with AI systems.
- Ability to design and manage data architectures for large-scale, multi-tenant environments.
- Experience applying ML or automation to security or operational intelligence domains.
- A builder’s mindset — passionate about shipping scalable, practical AI systems.
Benefits
- Discretionary bonus program
- Paid time off
- Flexible work arrangements
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
PythonMachine Learning EngineeringData EngineeringML pipelinesLLM technologiesRAG architecturesAPI integrationdata architecturesautomationMLOps
Soft Skills
collaborationproblem-solvingcommunicationadaptabilitycreativitycritical thinkingattention to detailproject managementanalytical thinkingbuilder's mindset