[Hiring] Data Scientist, Data Intelligence @World Vision Canada

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).