Staff Data Scientist

Clio • Vancouver, BC

48d • Hybrid

About The Position

Clio is the global leader in legal AI technology, empowering legal professionals and law firms of every size to work smarter, faster, and more securely. We are transforming the legal experience for all by bettering the lives of legal professionals while increasing access to justice. Summary: Job Duties Architectural Strategy & Forecasting Leadership: Define the long-term forecasting roadmap and establish architectural standards for the entire company. Lead the architectural design of complex ML systems, ensuring they are scalable, maintainable, and integrated seamlessly with the broader engineering stack. Architect reusable, "platform-level" forecasting frameworks to be used by other Data Science teams. High-Impact Modeling: Own the development of "tier-1" models—those with the highest business risk or technical complexity—using advanced statistical, deep learning, or Reinforcement Learning techniques. Tackle high-ambiguity challenges, such as integrating causal inference or deep learning into global forecasts. GenAI & LLM Innovation: Act as the subject matter expert for Generative AI; design RAG architectures, evaluate foundation models, and establish fine-tuning protocols for proprietary data. MLOps & Quality Assurance: Define the team’s technical standards for CI/CD, model versioning, and automated testing. Audit codebases to ensure high-performance and "production-ready" quality. Strategic Experimentation: Own the end-to-end design and evaluation of high-impact product and business experiments, establishing rigorous statistical standards and frameworks to ensure trustworthy, data-driven decisions. Technical Mentorship & Influence: Provide deep technical guidance to more junior Data Scientists. Influence the roadmap by identifying "blind spots" in current data strategy and proposing novel solutions. Cross-Functional Translation & Ethics: Partner with Data Engineering to optimize data pipelines for ML and with Product to ensure technical feasibility of the long-term vision. Lead the implementation of Model Interpretability (XAI) frameworks to ensure all automated decisions are transparent and unbiased.

Requirements

• 8+ years of experience in Data Science, Machine Learning, or a highly quantitative field, with a track record of deploying models that drove significant revenue or cost savings.
• Mastery of System Design and state-of-the-art time-series research.
• Leadership without Authority: Proven ability to influence executive leadership and mentor senior technical staff.
• Proven ability to lead large-scale technical projects across multiple teams without being a direct people manager.
• Deep Technical Stack: Expertise in Python and SQL. Advanced experience with AWS and Databricks. Proficiency in distributed computing (e.g., Spark, Ray) and modern data platforms (Snowflake/Databricks).
• Modern AI Toolkit: Hands-on experience with LLM orchestration (LangChain, Haystack), vector databases, and PyTorch or TensorFlow.
• System Design: Strong understanding of software engineering principles (microservices, API design) as they relate to deploying ML at scale.
• Master’s or PhD in Computer Science, Physics, Statistics, Mathematics, or a related quantitative field.
• Communication: Ability to persuade executive leadership on technical investments and "sell" a long-term technical vision.

Responsibilities

• Define the long-term forecasting roadmap and establish architectural standards for the entire company.
• Lead the architectural design of complex ML systems, ensuring they are scalable, maintainable, and integrated seamlessly with the broader engineering stack.
• Architect reusable, "platform-level" forecasting frameworks to be used by other Data Science teams.
• Own the development of "tier-1" models—those with the highest business risk or technical complexity—using advanced statistical, deep learning, or Reinforcement Learning techniques.
• Tackle high-ambiguity challenges, such as integrating causal inference or deep learning into global forecasts.
• Act as the subject matter expert for Generative AI; design RAG architectures, evaluate foundation models, and establish fine-tuning protocols for proprietary data.
• Define the team’s technical standards for CI/CD, model versioning, and automated testing.
• Audit codebases to ensure high-performance and "production-ready" quality.
• Own the end-to-end design and evaluation of high-impact product and business experiments, establishing rigorous statistical standards and frameworks to ensure trustworthy, data-driven decisions.
• Provide deep technical guidance to more junior Data Scientists.
• Influence the roadmap by identifying "blind spots" in current data strategy and proposing novel solutions.
• Partner with Data Engineering to optimize data pipelines for ML and with Product to ensure technical feasibility of the long-term vision.
• Lead the implementation of Model Interpretability (XAI) frameworks to ensure all automated decisions are transparent and unbiased.

Benefits

• Competitive, equitable salary with top-tier health benefits, dental, and vision insurance
• Hybrid work environment, with expectation for local Clions (Vancouver, Calgary, Toronto, Dublin and Sydney) to be in office min. twice per week.
• Flexible time off policy, with an encouraged 20 days off per year.
• $2000 annual counseling benefit
• RRSP matching and RESP contribution
• Clioversary recognition program with special acknowledgement at 3, 5, 7, and 10 years

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 251-500 employees