Data Scientist - Sonatype

About the Role

Sonatype is seeking a Data Scientist to join our AI & Data Science team. You will act as an internal AI consultant and technical lead, collaborating across product, engineering, and security teams to apply machine learning and generative AI to real-world challenges—ranging from malicious behavior detection to developer-facing GenAI experiences.

This role is ideal for a practitioner who thrives on autonomy, enjoys translating ambiguous ideas into scalable systems, and prefers working across boundaries rather than staying in a single product lane.

What You'll Do

• Lead Applied AI Projects: Prototype, validate, and deploy practical ML and GenAI solutions from concept to impact.
• Internal Consulting: Scope problems, evaluate approaches, and advise on ML/AI best practices across the organization.
• Model Development: Research and deploy models for malicious behavior detection, anomaly detection, and fraud analysis using classical ML, LLMs, embeddings, RAG, and agentic workflows.
• Experimentation: Design robust experiments and establish evaluation pipelines for model reliability, accuracy, and business impact.
• Bridge Research to Production: Translate research insights into scalable APIs, tools, and workflows.
• Stakeholder Collaboration: Communicate technical tradeoffs clearly to both technical and non-technical stakeholders; mentor peers to elevate AI literacy.
• Governance: Partner with data governance teams to ensure compliance with privacy regulations and ethical standards.

What You Bring

• 5+ years of hands-on experience in applied data science, ML, or AI research.
• Strong Python skills and experience with libraries/platforms such as Databricks and scikit-learn.
• Proven experience shipping ML or GenAI applications from prototype to production.
• Deep familiarity with modern LLM ecosystems (OpenAI, Anthropic, Hugging Face, open-weight models).
• Experience building agentic or multi-step AI workflows (LangGraph, LangChain, Semantic Kernel).
• Strong evaluation mindset: defining quality metrics, building evaluation datasets, and assessing reliability.
• Proficiency with Git, testing, code review, and collaborative software development.
• Computer Science or equivalent technical degree strongly preferred.

Bonus Points

• Strong MLOps experience (MLflow, CI/CD, model monitoring).
• Experience operating ML/GenAI systems at scale (observability, tracing, drift detection).
• Familiarity with cybersecurity, fraud detection, or software supply-chain security.
• Experience with PySpark and production data pipelines.