AI Data Scientist

This position is listed on behalf of a partner company, which manages all applications and next steps. Our partner is looking for an AI Data Scientist based in Canada. We are seeking an experienced AI Data Scientist to research, develop, and deploy advanced natural language processing (NLP), machine learning, and generative AI solutions for complex business applications. In this role, you will transform unstructured documents and large-scale datasets into reliable insights that support smarter commercial decisions. You will combine deep scientific expertise with hands-on engineering to take innovative ideas from early experimentation to production-ready systems. Working closely with engineering, product, and data science teams, you will shape AI capabilities, improve model performance, and establish rigorous evaluation standards. This is an opportunity to influence the direction of AI-powered products while mentoring colleagues and contributing to a collaborative, research-driven environment focused on practical innovation and measurable impact. Accountabilities - Research and evaluate emerging techniques in NLP, statistical machine learning, deep learning, and generative AI, translating promising advances into practical product capabilities. - Independently investigate complex technical challenges, develop hypotheses, conduct experiments, and compare alternative models, architectures, and methodologies. - Design and implement NLP and machine learning solutions using appropriate algorithms, representations, and transformer-based architectures. - Develop data pipelines, preprocessing workflows, feature representations, embeddings, and training datasets for structured and unstructured information. - Establish data quality practices that maintain model reliability as datasets, applications, and business requirements evolve. - Build generative AI and large language model solutions using prompt engineering, retrieval-augmented generation (RAG), embeddings, vector search, fine-tuning, AI agents, and structured generation.

- Optimize model selection and performance by balancing accuracy, latency, computational cost, and business requirements. - Design rigorous experiments, benchmarks, evaluation datasets, and statistical methodologies to measure model quality and identify opportunities for improvement. - Conduct detailed error analysis and apply relevant evaluation metrics to guide model refinement and support evidence-based decisions. - Move AI solutions from research and prototyping into production, collaborating with engineering teams to ensure scalability, reliability, monitoring, and ongoing optimization. - Monitor deployed systems for model drift, quality issues, and performance bottlenecks, implementing improvements as needed. - Partner with product, engineering, and data science stakeholders to shape technical direction and align AI capabilities with business objectives. - Provide technical leadership and mentorship in NLP, machine learning, generative AI, and experimental design while promoting scientific rigor and continuous learning. Requirements: - A master’s degree in computer science, data science, computational linguistics, statistics, mathematics, engineering, or a related quantitative discipline. A PhD is preferred but not required. - At least 10 years of professional experience in data science, machine learning, NLP, or AI, including substantial hands-on experience developing and deploying NLP or generative AI solutions. - Demonstrated success taking machine learning, NLP, or generative AI projects from experimentation through production deployment and continuous optimization. - Strong ability to translate open-ended research questions into practical solutions with measurable business and product outcomes.