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.

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.
Education: 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.

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

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningDeep LearningReinforcement LearningStatistical ModelingSystem DesignTime-Series AnalysisPythonSQLDistributed ComputingMLOps

Soft Skills

Leadership without AuthorityTechnical MentorshipInfluencingCommunicationCross-Functional CollaborationStrategic ExperimentationProblem SolvingTechnical GuidanceData-Driven Decision MakingAdaptability

Certifications

Master’s in Computer SciencePhD in Computer ScienceMaster’s in PhysicsMaster’s in StatisticsMaster’s in Mathematics