Data Scientist - Remote

Overview

At Silent Eight, we develop our own AI-based products to combat financial crimes that enable things like money laundering, the financing of terrorism, and systemic corruption. We’re a leading RegTech firm working with large international financial institutions such as Standard Chartered Bank and HSBC. Join us and help make the world a safer place!

In Short

• Lead the data science lifecycle, from discovery and exploration to delivery and customer hand-off.
• Translate ambiguous business problems into clear problem statements and deliver working, production-ready solutions.
• Partner with customers and internal stakeholders to co-design use cases, define success criteria, and ensure models are adopted and successful in production.
• Build quick, iterative prototypes to test ideas, and work cross-functionally to deploy validated solutions into production environments.
• Own and improve pipelines for data integration, validation, and monitoring, ensuring long-term stability and performance.
• Analyze large-scale structured and unstructured datasets to extract insights and power model development.
• Apply machine learning, NLP, graph analytics, and other advanced techniques to solve challenging problems such as semantic search, or anomaly detection.
• Create and maintain internal data science tooling to streamline experimentation, testing, and delivery.
• Support internal teams and customers with issue resolution, ensuring data science solutions continue to deliver value post-deployment.
• Follow and advocate for best practices in MLOps, DataOps, and clean code to ensure reproducibility, maintainability, and scalability.

Requirements

• Based in Canada (remote-first team; flexible working environment).
• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field.
• Demonstrated experience with LLM technologies (LangChain, LlamaIndex, OpenAI APIs, etc.) and building NLP applications.
• Deep proficiency in Python: you write clean, modular, maintainable, and testable code suitable for real-world deployments.
• Solid SQL skills and hands-on experience with large-scale data (e.g., PySpark, BigQuery).
• Skilled in graph analysis, machine learning, and unstructured data workflows.
• Demonstrated ability to apply software engineering best practices (e.g., modular design, clean code, unit testing, CI/CD) in data science and machine learning projects, ensuring production-readiness and maintainability.
• Ability to drive end-to-end initiatives, from exploration to delivery, where solutions must be state-of-the-art, business-aligned, and regulatory-compliant.
• Comfortable working in Linux environments and using collaborative tools (e.g., Git, Docker).
• Strong communication skills—translate technical complexity into actionable business narratives, driving clarity, alignment, and decision-making across all levels of the organization.
• Mindset of ownership: you’re excited to see projects through, from first prototype to deployed, customer-facing solution.

Benefits

• Full time employment
• Employee benefits
• Work-life balance: flexible working hours, remote work forever
• Career growth: Promotion and great development opportunities within the organization