Data Scientist

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Sonatype

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2008

🔒 Cybersecurity

☁️ SaaS

💰 $80M Private Equity Round on 2018-09

Cybersecurity • Software • SaaS

Sonatype is a leader in software composition analysis (SCA) and software supply chain management. The company provides solutions to automate software supply chain security, build centralized components, control open source risks, and simplify software bill of materials (SBOM) compliance. Sonatype offers tools such as Nexus Repository, Repository Firewall, Lifecycle, and SBOM Manager, which help developers deliver quality code securely and manage vulnerability risks. Sonatype integrates with numerous tools and languages, supporting dev, security, and ops teams to ensure secure deployments. The company is recognized for its end-to-end software supply chain solutions that leverage artificial intelligence to predict and intercept malicious components, enhancing security across industries such as financial services and technology.

📋 Description

• Lead applied AI projects from concept to impact by prototyping, validating, and helping teams deploy practical ML and GenAI solutions • Act as an internal consultant across product, engineering, security, and research teams • Scope problems, evaluate approaches, and advise on ML/AI best practices and productive use of generative technologies • Lead research, development, and deployment of models for malicious behavior detection, anomaly detection, and fraud analysis • Design experiments and evaluation pipelines for model reliability, accuracy, and business impact • Bridge research and production by translating research insights into scalable APIs, tools, or workflows • Explore LLMs, embedding models, RAG, and agentic workflows to enhance developer and security experiences • Communicate technical concepts, tradeoffs, and recommendations through presentations, documentation, and collaboration • Mentor peers and help elevate organizational AI literacy and capabilities • Partner with the data governance team on data-privacy compliance and ethical considerations

🎯 Requirements

• 5+ years of hands-on experience in applied data science, machine learning, AI engineering, or AI research • Computer Science or equivalent technical degree strongly preferred • Strong Python skills • Practical experience with Databricks, LLM APIs, and scikit-learn • Experience building and shipping ML or GenAI applications from prototype through usable workflows • Deep familiarity with OpenAI, Anthropic/Claude, Hugging Face, and open-weight models • Ability to design LLM applications using prompting, context management, structured outputs, retrieval, and tool use • Experience building agentic or multi-step AI workflows with LangGraph, LangChain, Semantic Kernel, or similar frameworks • Experience defining quality metrics, building evaluation datasets, assessing reliability, and making data-driven tradeoffs • Comfort working with large, messy, structured, and unstructured data • Proficiency with Git, testing, code review, and collaborative software-development practices • Practical judgment for building maintainable, secure, dependable systems • Strong written and verbal communication skills across technical and non-technical partners • Strong MLOps experience, including MLflow or comparable tooling, experiment tracking, reproducible pipelines, versioning, CI/CD, serving, and production monitoring • Experience operating ML or GenAI systems at scale • Experience with Databricks ML, AWS SageMaker, Azure ML, or similar managed ML platforms • Familiarity with MCP, agent-tool integrations, LLM guardrails, and production safety practices • Experience with AI-assisted development tools such as Copilot, Claude Code, or Codex • Exposure to cybersecurity, fraud detection, anomaly detection, code analysis, or software supply-chain security • Experience with PySpark and production data pipelines • Experience working within a software product company or SaaS

🏖️ Benefits

• Parental leave • Diversity and inclusion working groups • Flexible working practices • Paid Volunteer Time Off (VTO)