Senior Data Scientist at Sonatype

The Opportunity●      We’re looking for a Senior Data Scientist to join our growing AI & Data Science team.●      You’ll operate as an internal AI consultant and technical lead, helping multiple teams across Sonatype apply machine learning and generative AI to real-world problems.●      You’ll explore complex datasets, design experiments, build models, and collaborate closely with product engineering, and security experts to turn research ideas into practical, scalable solutions.●      This role is ideal for someone who thrives on autonomy, loves translating ambiguous ideas into working systems, and enjoys working across boundaries rather than in a single product lane.

What You’ll Do

Lead applied AI projects from concept to impact — prototype, validate, and help teams deploy practical ML and GenAI solutions.

Collaborate cross-functionally: Partner with product, engineering, and research teams to scope problems, identify opportunities, and co-develop solutions.

Act as an internal consultant: Advise teams on ML/AI best practices, model evaluation, and productive use of generative technologies.

Design robust experiments and establish evaluation pipelines for model reliability, accuracy, and business impact.

Bridge research and production: Package research insights into usable APIs, tools, or workflows for other teams.

Explore new techniques (e.g., LLMs, embeddings models, retrieval-augmented generation, agentic workflows) to enhance developer and security experiences.

Share knowledge and mentor peers, helping elevate the organization’s AI literacy and capabilities.

What We’re Looking For

6+ years of experience in applied data science, machine learning, or AI research

Strong Python skills and hands-on experience with ML/AI libraries and platforms such as Databricks, OpenAI API, and Scikit-learn

Comfortable working with large, messy, or unstructured datasets — you know how to turn chaos into features, insights, and beautiful visualizations

Deep familiarity with LLMs and GenAI ecosystems (e.g. OpenAI, Claude, Hugging Face): skilled in prompt engineering, parameter tuning, and evaluating model behavior against ground truth

Experience taking ML or GenAI systems from prototype to production, even if small-scale or incremental

Strong analytical thinking, experimentation skills, and appreciation for trustworthy, data-driven evaluation

Proficiency with Git and collaborative code workflows (GitHub or similar)

A balanced mindset — equally comfortable exploring research ideas and implementing production-ready systems

Proactive and self-directed: you don’t wait for perfect specs; you find meaningful problems and drive them to completion

Bonus Points

Experience with AI-assisted coding tools (Copilot, Claude Code, Codex, etc.)

Familiarity with agentic workflows, Model Context Protocol (MCP), and tool-use integrations

Exposure to cybersecurity, anomaly detection, or code analysis

Understanding of MLOps practices (MLflow, AWS SageMaker, model serving, or monitoring)

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