Role Description As part of the Data Intelligence team, the Data Scientist strengthens decision-making in alignment with World Vision Canada’s mission and impact. The role delivers advanced analytics that enable confident action, improve experiences, and support digital enablement and innovation. - Designs and delivers end-to-end analytics solutions, from data sourcing and preparation through to development. - Applies statistical and machine-learning techniques to solve complex business problems. - Partners with cross-functional and technical teams to support deployment and maintenance. - Communicates insights clearly to drive understanding, adoption, and action. - Contributes to scalable, integrated solutions in a digital environment. - Advances insights-led decision-making and supports the Data Intelligence mandate. - Integrates diverse datasets and translates analysis into actionable insights. Responsibilities - Leads the design and development of advanced analytics solutions (e.g., customer lifetime value, churn prediction, segmentation). - Defines analytical approaches to ambiguous problems by partnering with stakeholders. - Sources, integrates, and prepares complex datasets from internal and external systems. - Applies statistical, machine learning, and data mining techniques to identify trends and patterns. - Enables deployment and ongoing performance of analytics solutions. - Translates analytics outputs into actionable recommendations through storytelling and data visualization. - Supports adoption and effective use of insights by guiding stakeholders. - Strengthens data trust and accessibility by contributing to well-structured data assets. - Identifies and implements improvements to analytical methods and tools. Qualifications - Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, Economics, or a related quantitative field, or equivalent experience. - 3–5 years of experience in data science or advanced analytics, including relevant academic research. - Strong foundation in statistics and machine learning, with experience applying techniques such as regression, classification, clustering, forecasting, and experimentation. - Strong Python or R (e.g. pandas, NumPy, scikit-learn) and SQL for working with large, complex datasets. - Experience working with modern data platforms (e.g. Azure, Snowflake). - Expertise in Natural Language Processing and applying domain knowledge to extract insights from unstructured data. - Experience designing and delivering end-to-end analytics solutions. - Ability to translate ambiguous business problems into analytical approaches and actionable insights. - Strong communication skills, with the ability to explain complex analysis clearly. - Certification in machine learning or big data and experience working in Agile environments considered assets. Benefits - Health Spending Account. - Up to 6% matched pension contributions. - Parental leave top-up. - Generous paid vacation, sick days, wellness and personal days. - Office closed extra days before long weekends (6x/year).

• As a Data Scientist, your mission will go far beyond the numbers: you will be challenged to translate complex business needs into predictive models and intelligent solutions. • In a strategic capacity, you will take a leading role in evolving our ecosystem of financial and digital products, creating direct, large-scale impact on our customers' lives.

• Own the technical architecture and engineering strategy for AutoQuote's cloud-native platform — spanning AI feature integration, data pipeline infrastructure, microservices design, and platform reliability. • Lead the design and delivery of the highest-complexity, highest-impact engineering initiatives on the team, setting the architectural patterns and engineering standards that guide the broader organization. • Define and enforce software quality standards, AI usage guidelines, and engineering best practices across the AutoQuote engineering organization. • Partner with engineering leadership, product management, and program stakeholders to translate program strategy into a coherent technical roadmap and prioritized backlog. • Evaluate, prototype, and champion emerging AI capabilities — including LLM integration, agentic frameworks, and AI-assisted development tooling — driving adoption across the team and into the product. • Drive responsible AI governance across AutoQuote, including prompt engineering standards, AI output evaluation practices, and compliance with Cisco security and data handling policies. • Mentor and technically develop senior and mid-level engineers; serve as the primary technical authority and critical issue point for complex engineering decisions. • Lead architecture reviews, critical design decisions, and cross-functional technical alignment sessions. • Represent AutoQuote engineering in program-level and executive forums; communicate technical tradeoffs, risks, and decisions with clarity to both technical and non-technical audiences.

• Own the design, development, evaluation, and optimization of AI and Machine Learning solutions that support Hyatt’s guest, colleague, and operational experiences. • Design, prototype, and productionize Generative AI solutions in NL Search, Information Retrieval and Recommender Systems. • Build and evaluate LLM-powered applications, including retrieval-augmented generation, prompt engineering, fine-tuning, embeddings, semantic search, and agentic or workflow-based AI systems. • Develop robust model evaluation frameworks, including offline metrics, human evaluation, guardrail testing, bias and safety checks, and business-impact measurement. • Partner with ML engineering and data engineering teams to deploy scalable real-time inference pipelines and batch processing workflows. • Mentor data scientists and ML practitioners through design reviews, code reviews, modeling best practices, and knowledge sharing. • Collaborate with ML engineering to productionize models and Gen AI services using AWS-native tools and modern MLOps practices.