• Be responsible for the entire end-to-end lifecycle of Artificial Intelligence solutions, from design and architecture to validation, deployment and availability for consumption via APIs, ensuring scalability, stability and high performance; • Develop, evaluate and optimize Machine Learning models and Generative AI applications, ensuring the technical quality of solutions and their alignment with business needs; • Continuously analyze the trade-off between computational cost and solution performance, considering factors such as token consumption, inference time, infrastructure usage and return on investment (ROI), and propose alternatives that maximize efficiency and value for the organization; • Implement governance, security and reliability mechanisms for AI applications, using strategies such as guardrails, response validation, quality monitoring and context-anchoring techniques, including Retrieval-Augmented Generation (RAG), to ensure accurate, safe and business-aligned responses; • Develop and maintain data pipelines and inference flows in collaboration with multidisciplinary teams, ensuring integration, observability and continuous monitoring of models in production; • Document architectures, models, experiments and processes to promote traceability, reproducibility and adherence to data and AI governance practices; • Collaborate with business and technology stakeholders to identify opportunities for AI application, translating complex challenges into scalable, high-impact analytical solutions; • Stay up to date with the evolution of technologies, frameworks and best practices related to Data Science, Machine Learning and Generative AI, proposing innovations that add value to the business.

• Establish and maintain enterprise-level data management practices aligned with Level 4–5 CMMI target operating maturity; formal appraisal not required • Identify authoritative data sources, standardize data definitions, resolve duplicate or conflicting data elements, fill metadata gaps, and address reporting inconsistencies across OAA applications, SQL Server 2022 databases, SSRS reports, Power BI, SharePoint, and Power Apps • Develop and maintain data dictionaries, metadata documentation, stored procedure inventories, and report-to-data-source traceability • Assist with data-related inputs for ATO documentation and audits • Propose master data management recommendations as part of the Task 2 portfolio review; no specific MDM platform is required, but any proposed approach must align with the Microsoft-based OAA environment and comply with VA security and ATO requirements • Propose data fabric or metadata-driven approaches, subject to Government approval

Role Description As part of the Data Science Development team, you will contribute to the design and development of machine learning–powered solutions that bring added value and new capabilities to our suite of large-scale software products. - Analyzing new challenges and applying critical thinking to propose innovative software solutions. - Taking ownership of all stages of the design and development of applications that leverage statistical methods or machine learning, including: - Data manipulation and transformation; - Model selection, training, and validation; - Implementation and integration into our software product suite. - Documenting and testing developments. - Providing technical support to deployment, development, and project teams that use the features developed by your team. - Staying up to date with the latest advances in data science. Qualifications - You have completed a Master’s or Ph.D. degree in Artificial Intelligence, Machine Learning, Data Science, or a related field. - You have at least 5 years of relevant experience in data science or a similar role. - You have strong knowledge of applying statistical, machine learning, and deep learning techniques to solve real-world prediction and natural language processing challenges. - You have a solid understanding of MLOps practices. - You have experience integrating large language models (LLMs) and/or agentic AI into software solutions (prompting techniques, RAG, MCP). - You enjoy and are highly proficient in Python programming (knowledge of C++ is considered an asset). - You have excellent communication skills, particularly when it comes to explaining complex technical concepts to non-technical audiences. - You possess strong analytical and problem-solving skills. - You enjoy working as part of a team and thrive in a collaborative environment. - You are fluent in French, both spoken and written. Benefits - Flexible working hours, including remote work for a balanced life. - Team activities and annual traditions that we take pride in. - Everyday support: Employee assistance program, telemedicine, and mental health support. - Training and professional development opportunities to grow, learn and discover your way forward. Employment Conditions Candidates must be legally authorized to work in the selected country at the time an offer of employment is made. It is the sole responsibility of candidates to obtain any required work permits, visas, or other authorizations prior to their start date. In accordance with the standards and regulatory requirements to which GIRO adheres, all positions—whether permanent, fixed-term, or internship—are subject to a criminal background check. Positions that involve access to financial data are also subject to a credit check. All verifications are conducted in accordance with GIRO’s established procedures.

Role Description We are looking for a Lead Data Scientist with strong expertise in Large Language Models (LLMs) and Python to design AI-powered chatbot solutions for specialized use cases. The ideal candidate brings a solid foundation in Natural Language Processing (NLP) and Conversational AI, along with hands-on experience in hallucination prevention, Responsible AI and compliance, and data analysis. - Team up with cross-functional groups spanning product, analytics, and engineering to build and refine a shopping assistant chatbot. - Craft and enhance prompt engineering strategies to elevate chatbot interactions. - Build LLM-based agents that connect with APIs, databases, and external tools through function calling. - Safeguard chatbot reliability and prevent hallucinations by applying model evaluation techniques. - Use A/B testing frameworks to measure and steadily improve chatbot performance. - Apply Responsible AI and compliance principles to secure ethical and regulatory alignment. - Perform exploratory data analysis to uncover insights and prepare structured requirements for the data engineering team. - Advise cloud engineering teams on the infrastructure needs behind AI-powered chatbot solutions. Qualifications - No less than 5 years of hands-on professional experience in data science. - At least 1 year of experience in people management or team leadership, covering a team of 5 or more FTEs. - Deep expertise in LLMs, including work with OpenAI APIs on Azure. - Strong Python capabilities for integrating and optimizing AI workflows. - Practical background in creating AI agents that use function calling to interact with external tools and databases. - Familiarity with hallucination prevention techniques for ensuring chatbot accuracy and reliability. - Solid grasp of Responsible AI and compliance best practices, including ethical AI guidelines. - Experience in Natural Language Processing (NLP) and Conversational AI development. - English at B2 level or higher, with strong written and spoken communication skills. Requirements - Applied experience with A/B testing and experimentation in close partnership with analytics teams. - Ability to shape and roll out a testing strategy that leverages key performance metrics for chatbots. - Proficiency in exploratory data analysis (EDA) to extract insights from data. - Skill in defining and communicating data requirements to the data engineering team. - Awareness of cloud services, either through hands-on experience or the capability to specify requirements for cloud engineering teams.