Data Scientist

Silent Eight Pte. Ltd.; Toronto; Remote; CAD 80,000 - 120,000; Full time

Job summary

A leading RegTech firm in Toronto is seeking a Data Scientist to own the end-to-end development of data solutions. The role involves leading the data science lifecycle, applying machine learning and NLP techniques to tackle financial crime-related challenges. Ideally, candidates should have a degree in a relevant field and expertise in Python and SQL. The company offers full-time employment with flexible remote work options and opportunities for career growth.

Benefits

Employee benefits

Work-life balance with flexible working hours

Career growth opportunities

Qualifications

• Experience with LLM technologies and building NLP applications.
• Ability to apply software engineering best practices in data science projects.
• Strong communication skills to translate technical complexity into actionable business narratives.

Responsibilities

• Lead the data science lifecycle from discovery to delivery.
• Translate ambiguous business problems into clear problem statements.
• Analyze large-scale structured and unstructured datasets for insights.

Skills

Machine Learning

Natural Language Processing (NLP)

Python

SQL

Graph Analysis

Data Validation

Education

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field

Tools

PySpark

BigQuery

Git

Docker

Job description

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!

As a Data Scientist, you will own the end-to-end development of data solutions — from understanding business problems to deploying and maintaining models in production. You’ll work closely with customers and internal teams to build impactful, scalable solutions using machine learning, NLP, and other advanced techniques.

Responsibilities

• 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.

We offer:

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