Data Scientist

This is a fully remote position, open to applicants in Canada.

📋 Description

• Oversee applied AI initiatives from inception to realization by prototyping, validating, and assisting teams in implementing effective ML and GenAI solutions.

• Serve as an internal advisor collaborating with product, engineering, security, and research teams.

• Define challenges, assess methodologies, and provide guidance on ML/AI best practices and the effective utilization of generative technologies.

• Direct the research, development, and deployment of models aimed at detecting malicious behavior, identifying anomalies, and analyzing fraud.

• Create experiments and evaluation frameworks to ensure model reliability, accuracy, and business impact.

• Connect research with production by converting research findings into scalable APIs, tools, or workflows.

• Investigate LLMs, embedding models, RAG, and agentic workflows to improve developer and security experiences.

• Articulate technical concepts, trade-offs, and recommendations through presentations, documentation, and collaborative efforts.

• Guide peers to enhance the organization’s AI literacy and capabilities.

• Collaborate with the data governance team on data privacy compliance and ethical considerations.

⛳️ Requirements

• A minimum of 5 years of practical experience in applied data science, machine learning, AI engineering, or AI research.

• A degree in Computer Science or a related technical field is highly preferred.

• Proficient in Python programming.

• Hands-on experience with Databricks, LLM APIs, and scikit-learn.

• Proven track record of developing and deploying ML or GenAI applications from prototype to functional workflows.

• Extensive knowledge of OpenAI, Anthropic/Claude, Hugging Face, and open-weight models.

• Capability to design LLM applications utilizing prompting, context management, structured outputs, retrieval, and tool usage.

• Experience in constructing agentic or multi-step AI workflows using LangGraph, LangChain, Semantic Kernel, or similar frameworks.

• Skilled in defining quality metrics, creating evaluation datasets, assessing reliability, and making data-informed trade-offs.

• Comfortable navigating large, complex, structured, and unstructured data.

• Proficient with Git, testing, code review, and collaborative software development methodologies.

• Possess sound judgment for developing maintainable, secure, and reliable systems.

• Exceptional written and verbal communication abilities with both technical and non-technical stakeholders.

• Strong MLOps expertise, including experience with MLflow or similar tools, experiment tracking, reproducible pipelines, versioning, CI/CD, serving, and production monitoring.

• Experience managing ML or GenAI systems at scale.

• Familiarity with Databricks ML, AWS SageMaker, Azure ML, or comparable managed ML platforms.

• Knowledge of MCP, agent-tool integrations, LLM guardrails, and best practices for production safety.

• Experience utilizing AI-assisted development tools such as Copilot, Claude Code, or Codex.

• Background in cybersecurity, fraud detection, anomaly detection, code analysis, or software supply-chain security.

• Proficient in PySpark and production data pipelines.

• Experience working in a software product company or SaaS environment.

🏝️ Benefits

• Parental leave.

• Diversity and inclusion working groups.

• Flexible working arrangements.

• Paid Volunteer Time Off (VTO).