Data Scientist developing AI agents and advanced analytics solutions for Ciena. Focused on machine learning, generative AI, and delivering business value through intelligent data - driven tools.
About the role
- Staff Data Scientist at Clio developing scalable ML systems and strategic experimentation frameworks. Leading high-impact modeling projects and mentoring junior team members.
Responsibilities
- 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
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