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Artefact

Data and AI-driven business transformation consulting

Senior AI & Data Scientist

Applied Machine Learning +1Confirmed live in the last 24 hours
Full-timeMontreal, QC, CanadaNo salary listedIn-person

About the Job

Requirements

  • The candidate must have 3–5 years of relevant data science experience and a substantial quantitative skill set.
  • The candidate must have strong knowledge of statistics and machine learning algorithms, including proven experience developing and deploying models.
  • The candidate must be proficient in Python, including scikit-learn and XGBoost; PyTorch is a strong plus, and the candidate must have solid SQL skills.
  • The candidate must have hands-on experience with large language models, such as evaluation, retrieval-augmented generation, or fine-tuning experiments; substantial personal projects qualify.
  • The candidate must specialize in at least one major AI platform ecosystem—Google (Gemini, Vertex AI), Anthropic (Claude), or OpenAI—and be familiar with a cloud platform such as Google Cloud Platform, Azure, or AWS.
  • The candidate should be comfortable using AI-assisted development tools such as Claude Code, Gemini CLI, or Cursor.
  • The candidate must have a Master's degree or higher in statistics, mathematics, engineering, computer science, economics, or a related field, or equivalent experience.
  • The candidate should be able to present methodology and results to non-technical audiences.

Responsibilities

  • Translate business and marketing challenges into analytical use cases with clear hypotheses and success metrics.
  • Develop statistical and machine learning models, including regression, forecasting, classification, clustering, and causal inference.
  • Select techniques based on business context, constraints, and data availability, and justify those choices.
  • Deliver production-ready solutions, including model training, deployment, monitoring, and ongoing refinement.
  • Run fine-tuning experiments, including dataset curation, supervised fine-tuning, LoRA/PEFT, and rigorous evaluation against baselines.
  • Build evaluation suites for large language model systems, including benchmarks, LLM-as-judge patterns, and regression tests.
  • Work with embeddings and retrieval where they affect answer quality.
  • Contribute to model selection decisions by weighing prompting, retrieval-augmented generation, and fine-tuning against cost, quality, and latency.
  • Build data pipelines for ingestion, transformation, and quality assurance across diverse data sources.
  • Create visualizations and dashboards that support data storytelling and decision making.
  • Present findings to client stakeholders, translating methodology into business language.
  • Mentor junior data scientists and use AI-assisted tools such as Claude Code and Gemini CLI to improve team productivity.

Desired Qualifications

  • Experience with causal inference, time series, or advanced statistics.
  • Experience with Hugging Face Transformers, LoRA/PEFT, or open-weight models.
  • Exposure to MLOps, including model versioning, pipelines, and monitoring.
  • Cloud certifications, especially Google Cloud Professional Machine Learning Engineer.

About the Company

Artefact

Data and AI-driven business transformation consulting

Artefact helps organizations use data and AI to transform their operations and decision-making. It provides end-to-end services across the data value chain, from strategy and data platform implementation to governance, advanced analytics, and sector-specific AI tools, delivered through consulting and project execution. The company works with industries like FMCG, retail, and luxury goods to optimize marketing performance, customer engagement, and ROI. Artefact differentiates itself by combining consulting expertise with data science and AI capabilities across multiple regions, offering integrated, sector-focused solutions rather than just advisory services. The main goal is to help clients adopt data-driven approaches to improve efficiency, decision quality, and marketing results at scale.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Paris, France
Founded
1998

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