Senior Scientist Jobs in Quebec (NOW HIRING)

Company Overview

Jesta I.S. is a Canadian enterprise software company with over 55 years of experience delivering mission-critical solutions to retailers, wholesalers, and brand manufacturers worldwide. Our Vision Suite platform supports complex retail operations across merchandising, supply chain, inventory, commerce, and financial management for organizations in fashion, footwear, athletic, luxury, and specialty retail.

As part of our strategic investment in AI, Jesta is building a new generation of intelligent enterprise applications that combine predictive analytics, machine learning, generative AI, agentic AI, and computer vision directly within business workflows. Our AI Centre of Excellence develops production-grade AI solutions deployed against real client data, helping retailers make smarter decisions, automate complex processes, and unlock measurable business value at scale.

Position Summary

We are seeking a Senior Data Scientist with deep expertise across the full spectrum of modern AI - from classical predictive modelling to large language models, agentic AI systems, and computer vision. This is a senior individual contributor role requiring strong autonomous judgment, technical leadership, and the ability to define and execute complex AI workstreams with minimal supervision.

The successful candidate will take full ownership of our existing production AI stack - maintaining, improving, and scaling models and pipelines already in active client use - while contributing meaningfully to the development of new capabilities. You will work at the intersection of predictive modelling, generative AI, and enterprise software, with your work deployed against real client data at scale.

Key Responsibilities

Predictive Modelling & Demand Forecasting

• Design, develop, and optimize machine learning models for demand forecasting, inventory optimization, and pricing analytics.
• Perform exploratory data analysis (EDA), model diagnostics, and data quality assessments.
• Engineer advanced features including promotions, seasonality, holidays, stockouts, lag variables, external signals, and signal processing techniques.
• Design and execute model experiments, hypothesis testing, oracle testing, and statistical evaluations.
• Evaluate and benchmark forecasting approaches including LightGBM, Random Forest, Gradient Boosting, Deep Learning (PyTorch), DeepAR, ARIMA/SARIMA, Prophet, ensemble methods, and Croston/TSB.
• Own the full model lifecycle from development and backtesting to deployment, monitoring, drift detection, and retraining.

Large Language Models & Generative AI

• Design and implement LLM-powered applications using RAG, fine-tuning, prompt engineering, structured outputs, and vector databases.
• Build AI systems that securely interact with enterprise data through governed APIs.
• Evaluate and integrate commercial and open-source foundation models into production.
• Develop explainability and transparency mechanisms for enterprise AI solutions.

Agentic AI Systems & MCP

• Design and develop autonomous AI agents with multi-step reasoning and tool use.
• Build integrations using Model Context Protocol (MCP) and tool-calling architectures for ERP data access.
• Implement human-in-the-loop (HITL) workflows, role-based security, and approval mechanisms.
• Establish standards for reliability, traceability, and auditability of agentic systems.

APIs & Production AI Infrastructure

• Design Semantic Read APIs connecting AI models to ERP data securely and reliably.
• Build scalable batch inference and feature pipelines on AWS SageMaker and Azure ML.
• Contribute to CI/CD automation, model validation, and deployment pipelines.
• Collaborate with Data Engineering and MLOps teams on Dockerized deployments, APIs, monitoring, and scalable inference.
• Define standards for feature stores, data pipelines, and model versioning.
• Partner with IT and Security teams to ensure compliant AI deployments.

Computer Vision

• Develop and deploy computer vision solutions for product classification, visual merchandising, and image-based retail applications.
• Integrate multimodal vision capabilities into forecasting and AI agent workflows.
• Evaluate and apply modern computer vision architectures to production use cases.

Product Ownership & Continuous Improvement

• Own and maintain production AI models and pipelines while driving continuous optimization.
• Balance maintenance of existing solutions with development of new AI capabilities.
• Identify and remediate technical debt, performance bottlenecks, and scalability issues.
• Serve as the technical owner for AI model performance and production incident resolution.

Documentation & Knowledge Sharing

• Maintain comprehensive documentation for models, pipelines, and experiments.
• Ensure reproducibility through experiment tracking, Git version control, and model lineage.
• Share knowledge through code reviews, technical documentation, and internal presentations.
• Contribute to R&D documentation and formal technical specifications.

Technical Leadership

• Independently scope, design, and deliver AI solutions with minimal supervision.
• Mentor team members through code reviews and architectural guidance.
• Translate business problems into robust AI solutions and communicate results to technical and business stakeholders.
• Apply responsible AI principles, including fairness, transparency, and model risk management.

Qualifications

Education

• PhD in Artificial Intelligence, Data Science, Computer Science, or a related quantitative field strongly preferred.
• Candidates with a Master's degree and exceptional industry experience will also be considered.

Experience

• Minimum 5 years of industry experience in applied data science (excluding academic research, internships, and research positions).
• Proven experience deploying and maintaining production-scale ML systems.
• Experience owning existing AI platforms as well as developing new capabilities.
• Hands-on expertise with LLMs and Generative AI, including RAG, prompt engineering, structured outputs, and evaluation frameworks.
• Experience building agentic AI systems with tool use, orchestration, and multi-step reasoning.
• Working knowledge of MCP or comparable agent orchestration frameworks.
• Experience developing and deploying computer vision models.
• Demonstrated ability to independently lead complex technical initiatives.
• Experience in commercial demand forecasting or time series modelling is a strong asset.
• Experience with signal processing techniques is an asset.
• Experience with ERP systems, retail data models, or supply chain data is an asset.

Technical Skills

• Advanced Python, including PyTorch, scikit-learn, LightGBM, XGBoost, TensorFlow/Keras, pandas, polars, NumPy, and LLM frameworks (LangChain, LlamaIndex, Anthropic/OpenAI SDKs); R is an asset.
• Forecasting libraries including Prophet, DeepAR, ARIMA/SARIMA, Croston/TSB, and ensemble methods.
• Experience with Kedro or similar workflow orchestration frameworks and large-scale batch processing.
• MLOps expertise including MLflow, Docker, CI/CD, Git, experiment tracking, model registries, drift detection, and retraining strategies.
• Experience with AWS (SageMaker, Lambda, S3, IAM, Batch), Azure ML, Azure DevOps, and Snowflake/Snowpark.
• REST API development and integration using frameworks such as FastAPI or Flask.
• Strong statistical foundations including time series analysis, Bayesian methods, causal inference, experimental design, and hypothesis testing.
• Advanced SQL for enterprise-scale analytics.

Soft Skills

• Highly autonomous with the ability to independently scope and deliver complex initiatives.
• Excellent written and verbal communication skills with technical and executive audiences.
• Strong analytical rigor and sound technical judgment.
• Collaborative mindset with cross-functional engineering and MLOps teams.
• Comfortable making decisions and driving outcomes in ambiguous environments.

Benefits

• Health coverage (medical, dental, disability, and life insurance)
• Wellness program (gym membership reimbursement)
• Professional growth (training platforms, career development fee subsidy, etc.)
• Company events
• Referral program
• Flexible schedule

Additional Information

• This is a hybrid role, 2 days working in the office in Montreal, QC is required.
• We thank all applicants for their interest. However, only shortlisted candidates will be contacted.

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Presentation de l'entreprise

Jesta I.S. est une societe canadienne specialisee dans les logiciels d'entreprise qui compte plus de 55 ans d'experience dans la fourniture de solutions strategiques aux detaillants, grossistes et fabricants de marques du monde entier. Notre plateforme Vision Suite prend en charge les operations complexes du commerce de detail dans les domaines du merchandising, de la chaine d'approvisionnement, de la gestion des stocks, du commerce et de la gestion financiere pour les entreprises des secteurs de la mode, de la chaussure, des articles de sport, du luxe et du commerce de detail specialise.

Dans le cadre de notre investissement strategique dans l'IA, Jesta developpe une nouvelle generation d'applications d'entreprise intelligentes qui integrent directement dans les flux de travail l'analyse predictive, l'apprentissage automatique, l'IA generative, l'IA agentique et la vision par ordinateur. Notre Centre d'excellence en IA developpe des solutions d'IA pretes a l'emploi, deployees sur les donnees reelles de nos clients, afin d'aider les detaillants a prendre des decisions plus eclairees, a automatiser des processus complexes et a generer une valeur commerciale mesurable a grande echelle.

Resume du poste

Nous recherchons un scientifique de donnees senior possedant une expertise approfondie dans tous les domaines de l'IA moderne - de la modelisation predictive classique aux grands modeles linguistiques, en passant par les systemes d'IA agentique et la vision par ordinateur. Il s'agit d'un poste de contributeur senior qui exige une grande autonomie de jugement, un leadership technique et la capacite de definir et de mener a bien des projets complexes en IA avec un minimum de supervision.

Le candidat retenu assumera l'entiere responsabilite de notre pile d'IA de production existante - en assurant la maintenance, l'amelioration et la mise a l'echelle des modeles et des pipelines deja utilises activement par nos clients - tout en contribuant de maniere significative au developpement de nouvelles capacites. Vous travaillerez a la croisee de la modelisation predictive, de l'IA generative et des logiciels d'entreprise, et vos travaux seront deployes a grande echelle sur les donnees reelles de nos clients.

Responsabilites Principales

Modelisation predictive et prevision de la demande

• Concevoir, developper et optimiser des modeles d'apprentissage automatique pour la prevision de la demande, l'optimisation des stocks et l'analyse des prix.
• Realiser des analyses exploratoires de donnees (EDA), des diagnostics de modeles et des evaluations de la qualite des donnees.
• Mettre en uvre des techniques avancees de creation de variables (promotions, saisonnalite, jours feries, ruptures de stock, variables de retard, signaux externes et traitement du signal).
• Concevoir et executer des experimentations, des tests d'hypotheses, des tests oracle et des evaluations statistiques.
• Evaluer et comparer differentes approches de modelisation (LightGBM, Random Forest, Gradient Boosting, PyTorch, DeepAR, ARIMA/SARIMA, Prophet, methodes d'ensemble, Croston/TSB).
• Gerer le cycle de vie complet des modeles : developpement, retrovalidation, deploiement, surveillance, detection de derive et reentrainement.

Grands modeles de langage (LLM) et IA generative

• Concevoir et developper des solutions basees sur les LLM (RAG, fine-tuning, prompt engineering, sorties structurees et bases de donnees vectorielles).
• Developper des systemes d'IA connectes aux donnees d'entreprise par l'intermediaire d'API gouvernees.
• Evaluer et integrer des modeles fondamentaux commerciaux ou open source en environnement de production.
• Mettre en place des mecanismes d'explicabilite et de transparence adaptes aux environnements d'entreprise.

Systemes d'IA agentique et MCP

• Concevoir et developper des agents autonomes capables de raisonnement en plusieurs etapes et d'utilisation d'outils.
• Developper des integrations utilisant le Model Context Protocol (MCP) ou des architectures similaires.
• Mettre en uvre des processus human-in-the-loop (HITL), des controles d'acces et des mecanismes d'approbation.
• Definir des standards de fiabilite, de tracabilite et d'auditabilite pour les systemes agentiques.

API et infrastructure IA de production

• Concevoir des API de lecture semantique securisees reliant les modeles d'IA aux donnees ERP.
• Developper des pipelines de traitement par lots pour l'inference, le calcul de variables et l'execution planifiee sur AWS SageMaker et Azure ML.
• Contribuer a l'automatisation CI/CD, aux validations et aux deploiements de modeles.
• Collaborer avec les equipes d'ingenierie des donnees et MLOps pour industrialiser les modeles (Docker, API, surveillance et inference a grande echelle).
• Definir des standards pour les pipelines de donnees, les feature stores et le versionnement des modeles.
• Collaborer avec les equipes TI et securite afin d'assurer des deploiements conformes et securises.

Vision par ordinateur

• Developper et deployer des modeles de vision par ordinateur pour des cas d'usage lies au commerce de detail.
• Integrer des capacites multimodales aux pipelines IA et aux modeles predictifs.
• Assurer une veille technologique sur les architectures de vision les plus recentes.

Gestion des produits IA et amelioration continue

• Assurer la responsabilite des modeles et pipelines IA en production, de leur stabilite et de leur amelioration continue.
• Contribuer a...