Senior Data Scientist

🔥 15 hours ago

🇨🇦 Canada – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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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

• Provide technical ownership for applied AI and data science initiatives across Sonatype • Lead complex AI projects from concept to production • Advise product, engineering, security, and research teams on ML and GenAI approaches • Lead research, development, and deployment of models for malicious behavior detection, anomaly detection, fraud analysis, and other security and product use cases • Design and guide GenAI solutions using LLMs, embeddings, retrieval-augmented generation, structured outputs, tool use, and agentic workflows • Establish experimentation and evaluation practices, including datasets, quality metrics, cross-validation, ground-truth evaluation, drift monitoring, and business-impact measurement • Set technical direction for reliable, secure, scalable, maintainable, and responsible AI systems • Design scalable APIs, services, tools, and workflows for AI adoption • Evaluate emerging AI technologies and frameworks and recommend adoption strategies • Partner with engineering and MLOps teams on deployment, observability, model lifecycle management, performance, and reliability • Mentor data scientists and technical contributors • Communicate AI strategy, technical tradeoffs, findings, and recommendations to technical and non-technical stakeholders • Partner with data governance, security, and legal stakeholders on privacy, security, ethical, and responsible-AI practices

🎯 Requirements

• 7+ 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 with LangGraph, LangChain, Semantic Kernel, or similar orchestration frameworks • Experience defining quality metrics and evaluation datasets • Experience working with large, messy, structured, and unstructured data • Proficiency with Git, testing, code review, and collaborative software-development practices • Strong written and verbal communication skills • Deep MLOps experience, including MLflow or comparable tooling, experiment tracking, reproducible pipelines, model/application versioning, CI/CD, serving, and production monitoring is desirable • Experience with Databricks ML, AWS SageMaker, Azure ML, or similar managed ML platforms is desirable • Experience applying ML or AI to cybersecurity, fraud detection, anomaly detection, code analysis, threat intelligence, or software supply-chain security is desirable

🏖️ Benefits

• Parental Leave Policy • Paid Volunteer Time Off (VTO) • Diversity & Inclusion Working Groups • Flexible working practices • Equal-opportunity employer • Disability or special-needs accommodation