Data Scientist, Data Intelligence
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Data Scientist, Data Intelligence
Location
Mississauga, ON, Canada
Experience
Mid
Posted
Jul 10, 2026
Apply by
August 9, 2026
Applicants
0
Early applicantFull-timeWork from Home
Job Description
Position:
Data Scientist, Data Intelligence
Reports to:
People Manager, Data Intelligence
Position Term:
Full Time Permanent
Primary Location:
Mississauga, Ontario, Canada
Workplace Type:
Remote (Within Canada)
Job Purpose
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.
Key responsibilities include designing and delivering end-to-end analytics solutions, from data sourcing and preparation through to development, ensuring data is reliable and fit for purpose throughout. The role applies statistical and machine-learning techniques to solve complex business problems, partners with cross-functional and technical teams to support deployment and maintenance, and communicates insights clearly to drive understanding, adoption, and action. The role contributes to scalable, integrated solutions in a digital environment.
Through this work, the Data Scientist advances insights-led decision-making and supports the Data Intelligence mandate to provide trusted data, reduce friction, and enable clear decisions. It brings strong capability in integrating diverse datasets, working within modern data environments, and translating analysis into actionable insights.
Responsibilities
Leads the design and development of advanced analytics solutions (e.g., customer lifetime value, churn prediction, segmentation) that address business priorities, producing models and outputs that are accurate, repeatable, and scalable
Defines analytical approaches to ambiguous problems by partnering with stakeholders to clarify objectives, shape hypotheses, and select appropriate methodologies
Sources, integrates, and prepares complex datasets from internal and external systems, proactively identifying new data sources for analytics models, and ensuring data quality, integrity, and readiness for analysis
Applies statistical, machine learning, and data mining techniques to identify trends, patterns, and drivers that inform strategic and operational decisions
Enables deployment and ongoing performance of analytics solutions by collaborating with technical and business teams to support production-grade implementation, workflow integration, and effective ongoing model monitoring and maintenance
Translates analytics outputs into actionable recommendations through clear storytelling, data visualization, and presentations tailored to diverse audiences
Supports adoption and effective use of insights by guiding stakeholders in interpreting results and applying them to decisions, planning, and performance management
Strengthens data trust and accessibility by contributing to well-structured data assets and practices that reduce friction in how data is accessed and used
Identifies and implements improvements to analytical methods and tools to increase efficiency, accuracy, and impact within a modern digital environment
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 (e.g. Master’s or PhD work)
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, prompt engineering, and applying domain knowledge to extract insights from unstructured data and translate LLM outputs into actionable recommendations
Experience designing and delivering end-to-end analytics solutions, from problem framing and data preparation through to model development
Ability to translate ambiguous business problems into analytical approaches and actionable insights
Strong communication skills, with the ability to explain complex analysis clearly and influence non-technical stakeholders
Certification in machine learning or big data and experience working in Agile environments considered assets
Why Consider Us?
Our competitive compensation & benefits include:
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)
World Vision Canada has consistently been awarded Canada and GTA top employer awards.
We are Canada’s largest development, relief, and advocacy non-profit organization.
We embody an Agile mindset here.
This is a current vacancy that we are actively recruiting for. The salary range represents the expected compensation for this role and is provided in accordance with Ontario’s pay transparency requirements under the Employment Standards Act.
Placement within the range will be determined based on relevant skills, experience, qualifications, and internal equity. The final offer will reflect the successful candidate’s background and demonstrated capabilities.
Key Responsibilities
- Design and develop advanced analytics solutions such as customer lifetime value and churn prediction models.
- Define analytical approaches for ambiguous business problems by partnering with stakeholders.
- Source, integrate, and prepare complex datasets from internal and external systems.
- Apply statistical, machine learning, and data mining techniques to identify trends and patterns.
- Enable deployment and ongoing performance of analytics solutions through collaboration with technical teams.
- Translate analytics outputs into actionable recommendations through storytelling and data visualization.
- Support adoption of insights by guiding stakeholders in interpreting results.
- Strengthen data trust by contributing to well-structured data assets and practices.
- Identify and implement improvements to analytical methods and tools.
Requirements
- Bachelor's degree in Data Science
- Statistics
- Mathematics
- Computer Science
- Engineering
- Economics
- or a related quantitative field
Skills Required
PythonRpandasNumPyscikit-learnSQLAzureSnowflakeNatural Language ProcessingPrompt EngineeringMachine LearningStatistical AnalysisData MiningRegressionClassificationClusteringForecastingExperimentationCommunicationStakeholder ManagementProblem SolvingCollaborationInfluence
Benefits
- Health Spending Account
- Up to 6% matched pension contributions
- Parental leave top-up
- Generous paid vacation
- Sick days
- Wellness days
- Personal days
- Office closed extra days before long weekends
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