Senior, AI & Data Science
HybridMontréal, Quebec, Canada
Job Summary
Own models end to end, from problem framing through production. Translate business challenges into analytical use cases with clear hypotheses and success metrics. Develop statistical and machine learning models including forecasting, classification, clustering, and causal inference. Ship production-ready solutions involving training, deployment, monitoring, and ongoing refinement. Run fine-tuning experiments and build evaluation suites for LLM systems using benchmarks and LLM-as-judge patterns. Build data pipelines for ingestion and quality assurance across diverse sources. Create visualizations and dashboards to support data storytelling. Present findings to client stakeholders and mentor junior data scientists.
Required Qualifications
- 3–5 years of relevant data science experience
- Substantial quantitative skill set
- Strong knowledge of statistics and ML algorithms
- Proven experience developing and deploying models
- Proficiency in Python (scikit-learn, XGBoost)
- Solid SQL
- Hands-on experience with LLMs: evaluation, RAG, or fine-tuning experiments
- Specialization in at least one major AI platform ecosystem — Google (Gemini, Vertex AI), Anthropic (Claude), or OpenAI
- Familiarity with a cloud platform (GCP, Azure, or AWS)
- Comfort with AI-assisted development tools such as Claude Code, Gemini CLI, or Cursor
- Excellent interpersonal and communication skills
- Master's degree (or higher) in statistics/mathematics, engineering, computer science, economics, or a related field, or equivalent experience
Desired Qualifications
- Causal inference, time series, or advanced statistics experience
- Hugging Face Transformers, LoRA/PEFT, or open-weight model experience
- MLOps exposure: model versioning, pipelines, monitoring
- Cloud certifications, especially Google Cloud Professional Machine Learning Engineer
- PyTorch
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