Senior AI & Data Scientist: End-to-End ML Leader

Artefact North America; Montreal (administrative region); Hybrid; CAD 120,000 - 190,000; Full time

Benefits offered by this job

Hybrid flexibility

Medical benefits

Unlimited paid time off

401(k) with company matching

Job summary

Artefact North America is hiring a Senior AI & Data Scientist to own end-to-end modeling—from framing problems to production. You will build models across forecasting, classification, clustering, and causal analysis, and guide junior scientists while delivering production-ready solutions.

Leverage embeddings, retrieval, and LLM evaluation; collaborate with clients to translate methodology into business value. Hybrid work supports flexible collaboration with teams.

Qualifications

• 3–5 years of data science experience with strong quantitative skills.
• Proficiency in Python (scikit-learn, XGBoost); PyTorch a plus.
• Hands-on experience with LLMs: evaluation, RAG, or fine-tuning.

Responsibilities

• Translate business challenges into analytical use cases with clear metrics.
• Develop statistical and machine learning models: regression, forecasting, classification, clustering, causal inference.
• Ship production-ready solutions: training, deployment, monitoring, refinement.
• Run fine-tuning experiments: dataset curation, SFT, LoRA/PEFT, evaluated against baselines.
• Build evaluation suites for LLM systems: benchmarks, regression tests.
• Build data pipelines for ingestion, transformation, QA across sources.
• Create visualizations and dashboards to tell the data story.
• Present findings to client stakeholders in business terms.
• Mentor junior data scientists and use AI-assisted tools to accelerate delivery.

Skills

Python

Statistics & ML

LLMs evaluation

Cloud platforms

Communication

Education

Master's degree in statistics/mathematics/CS/economics

Tools

Claude Code

Gemini CLI

Cursor

Job description

Artefact North America is hiring a Senior AI & Data Scientist to own end-to-end modeling—from framing problems to production. You will build models across forecasting, classification, clustering, and causal analysis, and guide junior scientists while delivering production-ready solutions.

Leverage embeddings, retrieval, and LLM evaluation; collaborate with clients to translate methodology into business value. Hybrid work supports flexible collaboration with teams.