DUTIES AND RESPONSIBILITES:
• Responsible for elicitation, analysis, and documentation of business requirements.
• Research and exploration of user requirements, costs, and benefits in support of documentation required for the demand management process.
• Responsible for analyzing the business needs to identify new processes and process improvements that will meet those needs.
• Documents current business processes and models to define requirements and/or gaps.
• Analyze detailed system factors including input/output requirements, information and paper flow, hardware, and software needs.
• Analyze “soft" system factors including roles, responsibilities, policy, culture, etc.
• Evaluate the impact of potential software and process changes on the organization.
• Develop and facilitate groups as necessary in pursuit of eliciting and defining requirements.
• Assist in the creation of the business case documentation.
• Understanding of architectural consistency and usability standards.
• Defines and develops user test cases and validates test results during testing.
• Executes unit and functional test cases.
• May conduct system demonstrations and training sessions, as well as participate in design/review of training content.
• Plays a third level support role by helping to troubleshoot and resolve issues with production systems.
• Participates in associate meetings and communicates any concerns to management.
QUALIFICATIONS AND REQUIREMENTS:
• Bachelor’s degree in computer science, Information Systems, Business, or another related field or equivalent work experience.
• Proven experience leading data migration requirements from legacy systems into a new ERP (Sage X3) environment
• Strong hands-on expertise in requirements elicitation, documentation, and management, with emphasis on data mapping, transformation rules, and validation
• Deep understanding of data structures, data quality, and migration best practices, with the ability to identify gaps and risks early
• Self-driven and accountable professional with strong stakeholder management and communication skills, able to drive outcomes with minimal oversight
• Working knowledge of Confluence and JIRA.
• Experience in any of the following business areas is desired: Sales operations, order entry, accounting, finance, procurement, warehouse operations, order management, and order fulfillment.
• Minimum of 3-5 years’ business analysis or systems analysis experience is preferred.
• Bonus: Sage X3 experience (ERP).
Associate is expected to operate at a proficient level across the following areas of technical knowledge and skill:
• Ability to organize and prioritize work.
• Detail oriented, proactive, creative, and efficient
• Intermediate level abilities in Excel, Outlook, PowerPoint, Visio, and Word
• Familiarity with application integration methods to include understanding of data mapping process.
• Ability to effectively work both independently and collaboratively in a team environment
• Ability to work on simultaneous and complex projects, with domain expertise in at least one business area.
• Expertise in ERP solution selection and implementation is a plus
• Ability to communicate effectively to both technical and non-technical audiences in written and non-written format
• Ability to work with all levels of associates
• Ability to work with minimal supervision in a very dynamic environment
• Ability to learn new systems and tools
• Knowledge of software development life cycle methodologies, processes, and procedures.
• Active listener
• Effective in a variety of formal/informal presentation settings: one-on-one, small, and large groups.
Job Title: Artificial Intelligence Specialist
Location: Montreal, QC
Duration: 12+ Months
This mandate aims at the implementation of artificial intelligence initiatives and solutions aimed at the design, development, industrialization, deployment, operation and evolution of artificial intelligence initiatives and solutions, including the data foundations necessary for their implementation.
Responsibilities:
- Design, develop, integrate, deploy and evolve artificial intelligence solutions, particularly in generative and agentic AI or in computer vision and MLOps;
- Analyze business and technical needs and recommend appropriate solutions;
- Develop and integrate models, AI capabilities and software components;
- To exploit, prepare and integrate the data necessary for the solutions;
- To establish the mechanisms for industrialization, deployment, monitoring, performance and quality of the solutions;
- Integrate AI solutions into application architectures, APIs and data platforms;
- Create prototypes, proofs of concept and functional increments to validate the chosen approaches;
- Participate in validation activities with users and various stakeholders;
- Document the solutions developed and ensure knowledge transfer to internal teams.
Requirements and qualifications
- Hold an undergraduate university degree (Bachelor's) in computer science, software engineering, artificial intelligence, data science or a related field;
- Possess a minimum of 6 to less than 9 years of relevant cumulative experience in developing artificial intelligence and data solutions, including experience in machine learning, data science, AI solution development and/or AI solution industrialization (MLOps), particularly in production environments.
- Possess relevant experience in Python development and in the development, integration or industrialization of AI solutions;
- Depending on the profile sought, possess specialized expertise in generative and agentic AI or in computer vision and MLOps;
- Have experience with data and AI platforms such as Databricks and Microsoft Azure, or equivalent technologies;
- Ability to work collaboratively with multidisciplinary teams and to simplify complex technical concepts.
- Languages / development: Python, SQL, PySpark /Spark, YAML, Bash/CLI, Git;
- Engineering, orchestration and deployment: Azure DevOps, VS Code, Databricks Notebooks/Repos/Jobs, Azure Data Factory, Terraform;
- Quality, traceability and observability: MLflow, traceability of executions and data, metrics, logs, monitoring and alerts;
- AI (ML models) and MLOps: MLflow, model registry, batch/real-time deployment, Feature Store, performance monitoring and tracking;
- Generative AI (LLM) and RAG: Azure AI Foundry / Azure OpenAI, Mosaic AI Gateway, vectorization and embeddings, vector databases and indexes, Azure AI Search, Vector Search, Cosmos DB;
- GenAI industrialization: endpoints and APIs, application development and integration (services, microservices), agents and orchestration, tools and connectors, MCPs, tracing and evaluation, safeguards and compliance, fine-tuning as needed
