Scientifique de données principal

Échelle Salariale (sans S’y Limiter)

118,

• Aménagements de travail flexibles et formule de travail hybride
• Possibilité d’acheter jusqu’à cinq jours de vacances additionnels par année
• Autres avantages sociaux visant à soutenir votre bien‑être mental et physique, incluant des soins de santé virtuels, un compte de dépenses bien‑être, et plus encore.
• RAAE et autres possibilités d’épargne : jusqu’à 12 % du salaire, voire plus (renseignez‑vous sur la possibilité d’un revenu de retraite garanti à vie)

Bonification annuelle cible, basée sur le salaire de base, avec un versement potentiel pouvant aller jusqu’au double de la cible (selon la performance individuelle de l’employé et les résultats financiers de l’entreprise).

12 %

Nos régimes de retraite sont flexibles et offrent une sécurité à long terme pour nos employés après leur carrière. Nous sommes l’une des rares entreprises à toujours offrir un régime de retraite à prestations déterminées qui assure un revenu de retraite garanti à vie.

Le salaire de la personne retenue pour ce poste sera déterminé selon un ensemble de facteurs, dont : l’expérience professionnelle, les compétences, la contribution anticipée quant au poste, l’équité interne, etc. L’échelle salariale présentée ci‑haut est pour une semaine de travail de 35 heures et pourrait s’appliquer à la majorité des différents profils de candidats, mais nous encourageons les candidats se situant en dehors de cette zone salariale à postuler.

We are seeking an experienced Data Scientist II (NLP / LLMs) to join our dynamic team. This role is hybrid, with candidates required to be based in Vancouver. You will collaborate with our advanced data science team to design, build, deploy, and iterate on production NLP solutions powered by Large Language Models (LLMs), GenAI, and agentic AI.

This role combines strong technical execution with a product mindset: understanding customer/stakeholder needs, defining success metrics, making informed trade‑offs, and delivering measurable business outcomes. The ideal candidate has deep NLP/LLM experience, thrives in ambiguity, and is comfortable operating in cloud environments (specifically AWS).

• Design and deliver end‑to‑end AI solutions for real business problems with a product mindset and measurable impact.
• Lead AI initiatives from discovery through implementation, testing, deployment, and monitoring, reducing risk in ambiguous problem spaces.
• Define hypotheses, KPIs and success metrics, run experiments, and iterate based on results.
• Partner with stakeholders to translate business needs into scalable technical solutions.
• Collaborate with data scientists, engineers, designers, and business SMEs to build and product ionize AI solutions on AWS.
• Serve as a technical lead and go‑to resource for the data science team, including architecture, approach, and technical quality.
• Analyze product and software usage patterns and recommend data‑driven improvements.
• Coach and mentor junior team members and lead by example in delivery and execution.
• Establish and uphold data science best practices, including coding standards, peer review, reproducibility, and testing.

• Master’s degree in Computer Science, Mathematics, AI, Engineering, or a related field, or equivalent practical experience.
• 5+ years of experience applying data science to product development, with deep focus on NLP, machine learning, and LLM‑based systems.
• Hands‑on experience with LLMs, including API integrations, prompt engineering, evaluation methods, and agentic patterns such as planning, tool or function calling, orchestration, and guardrails.
• Strong production experience in cloud environments, AWS preferred, including building and operating reliable NLP and LLM pipelines.
• Production proficiency with Python, Git and Git Hub, and CI or CD.
• Strong grounding in ML fundamentals and modern NLP and LLM techniques.
• Strong execution skills, including the ability to prioritize effectively, manage trade‑offs, and deliver in parallel across multiple work streams.
• Demonstrated ability to work effectively with stakeholders and cross‑functional teams to deliver outcomes.
• Experience defining and using KPI…