Senior Data Scientist
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Role Overview
Sonatype is seeking a Senior Data Scientist for its AI and Data Science team.
The role provides technical leadership across applied AI initiatives while remaining hands-on with data exploration, experiments, model development, and production delivery.
Use cases include malicious behavior detection, anomaly detection, fraud analysis, and developer- or analyst-facing GenAI experiences.
Key Skills for This Role
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About Sonatype
Sonatype develops software supply chain management and open-source security products, including Nexus Repository and tools for detecting malicious open-source software.
The company applies AI and machine learning to software quality, automation, security, and software supply chain use cases.
The role
Sonatype is seeking a Senior Data Scientist for its AI and Data Science team.
The role provides technical leadership across applied AI initiatives while remaining hands-on with data exploration, experiments, model development, and production delivery.
Use cases include malicious behavior detection, anomaly detection, fraud analysis, and developer- or analyst-facing GenAI experiences.
What you will do
- Own applied AI and data science initiatives and define approaches, architecture, priorities, and standards.
- Lead AI projects from concept to production and translate ambiguous problems into measurable experiments and scalable solutions.
- Advise product, engineering, security, and research teams on ML and GenAI opportunities.
- Develop and deploy models for security, fraud, anomaly detection, and product use cases.
- Design GenAI solutions using LLMs, embeddings, retrieval, structured outputs, tool use, and agentic workflows.
- Establish evaluation practices covering datasets, metrics, cross-validation, ground truth, drift, and business impact.
- Set direction for secure, scalable, maintainable, reliable, and responsible AI systems.
- Build scalable APIs, services, tools, and workflows for production AI adoption.
- Evaluate emerging AI frameworks and recommend adoption decisions.
- Partner with engineering and MLOps on deployment, observability, lifecycle management, performance, and reliability.
- Mentor technical contributors and improve AI engineering and data science practices.
- Communicate strategy and technical findings while supporting privacy, security, governance, legal, ethical, and responsible-AI practices.
What you bring
- At least 7 years of hands-on experience in applied data science, machine learning, AI engineering, or AI research.
- A Computer Science or equivalent technical degree is strongly preferred.
- Strong Python skills and practical experience with data and AI libraries or platforms such as Databricks, LLM APIs, and scikit-learn.
- Experience shipping ML or GenAI applications from prototype through usable internal or customer-facing workflows.
- Deep familiarity with LLM ecosystems including OpenAI, Anthropic or Claude, Hugging Face, and open-weight models.
- Ability to design LLM applications using prompting, context management, structured outputs, retrieval, and tool use.
- Experience with LangGraph, LangChain, Semantic Kernel, or similar frameworks for agentic or multi-step workflows.
- Strong evaluation skills, including quality metrics, representative datasets, reliability assessment, and data-driven tradeoffs.
- Comfort working with large, messy, structured, and unstructured data to produce features, insights, and visualizations.
- Proficiency with Git, testing, code review, and collaborative software development.
- Practical judgment for exploring emerging AI capabilities while building secure, dependable, maintainable systems.
- Proactive accountability and strong written and verbal communication across technical and non-technical partners.
Additional experience welcomed
- Deep MLOps experience with experiment tracking, reproducible pipelines, versioning, CI/CD, serving, and production monitoring is beneficial.
- Experience with ML platforms such as Databricks ML, AWS SageMaker, Azure ML, or comparable services is beneficial.
- Experience with AI architecture, reusable standards, MCP, guardrails, AI security, production safety, PySpark, or large-scale data pipelines is beneficial.
- Experience applying AI to cybersecurity, fraud, anomaly detection, code analysis, threat intelligence, or software supply-chain security is beneficial.
- Experience mentoring technical contributors or leading initiatives across multiple AI or data science teams is beneficial.
Company highlights
- Sonatype highlights recognition in software supply chain security, application security testing, AI compliance, open-source data solutions, and workplace innovation.
- Employee programs include Diversity and Inclusion Working Groups, parental leave, and paid volunteer time off.
About sonatype
Sonatype is a private software company helping enterprises secure and govern open-source and AI supply chains.
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