Job Opportunities API

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. -------------------- Présentation de l’entreprise Jesta I.S. est une société canadienne spécialisée dans les logiciels d'entreprise qui compte plus de 55 ans d'expérience dans la fourniture de solutions stratégiques aux détaillants, grossistes et fabricants de marques du monde entier. Notre plateforme « Vision Suite » prend en charge les opérations complexes du commerce de détail dans les domaines du merchandising, de la chaîne d'approvisionnement, de la gestion des stocks, du commerce et de la gestion financière pour les entreprises des secteurs de la mode, de la chaussure, des articles de sport, du luxe et du commerce de détail spécialisé. Dans le cadre de notre investissement stratégique dans l’IA, Jesta développe une nouvelle génération d’applications d’entreprise intelligentes qui intègrent directement dans les flux de travail l’analyse prédictive, l’apprentissage automatique, l’IA générative, l’IA agentique et la vision par ordinateur. Notre Centre d’excellence en IA développe des solutions d’IA prêtes à l’emploi, déployées sur les données réelles de nos clients, afin d’aider les détaillants à prendre des décisions plus éclairées, à automatiser des processus complexes et à générer une valeur commerciale mesurable à grande échelle. Résumé du poste Nous recherchons un scientifique de données senior possédant une expertise approfondie dans tous les domaines de l’IA moderne — de la modélisation prédictive classique aux grands modèles linguistiques, en passant par les systèmes 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 capacité de définir et de mener à bien des projets complexes en IA avec un minimum de supervision. Le candidat retenu assumera l’entière responsabilité de notre pile d’IA de production existante — en assurant la maintenance, l’amélioration et la mise à l’échelle des modèles et des pipelines déjà utilisés activement par nos clients — tout en contribuant de manière significative au développement de nouvelles capacités. Vous travaillerez à la croisée de la modélisation prédictive, de l’IA générative et des logiciels d’entreprise, et vos travaux seront déployés à grande échelle sur les données réelles de nos clients. Responsabilités Principales Modélisation prédictive et prévision de la demande • Concevoir, développer et optimiser des modèles d’apprentissage automatique pour la prévision de la demande, l’optimisation des stocks et l’analyse des prix. • Réaliser des analyses exploratoires de données (EDA), des diagnostics de modèles et des évaluations de la qualité des données. • Mettre en œuvre des techniques avancées de création de variables (promotions, saisonnalité, jours fériés, ruptures de stock, variables de retard, signaux externes et traitement du signal). • Concevoir et exécuter des expérimentations, des tests d’hypothèses, des tests « oracle » et des évaluations statistiques. • Évaluer et comparer différentes approches de modélisation (LightGBM, Random Forest, Gradient Boosting, PyTorch, DeepAR, ARIMA/SARIMA, Prophet, méthodes d’ensemble, Croston/TSB). • Gérer le cycle de vie complet des modèles : développement, rétrovalidation, déploiement, surveillance, détection de dérive et réentraînement. Grands modèles de langage (LLM) et IA générative • Concevoir et développer des solutions basées sur les LLM (RAG, fine-tuning, prompt engin