Analyste de données principal modernisant les plateformes et pipelines de données d’EDC, société financière publique canadienne. Traduction des besoins opérationnels en modèles, règles de transformation et récits utilisateurs.
About the role
- Business Data Analyst partnering with stakeholders to shape product decisions through experimentation and analysis. Driving measurable user experience outcomes within the Revenue Operations team in a hybrid role.
Responsibilities
- Collaborate closely with Product Owners and business stakeholders to design and plan experiments, define requirements, assumptions, and limitations
- Explore and analyze experiment data to understand customer behaviour, usage patterns, and performance drivers
- Propose, design, and evaluate experiments and causal analyses to answer well-scoped business questions
- Create new projects and manage multiple analytical initiatives informed by experiment results and emerging insights
- Conduct deep dive analyses to uncover trends, friction points, and opportunities
- Build dashboards and automated reports to improve accessibility and insight quality
- Translate business questions into measurable metrics
- Deliver data based recommendations and clearly identify actionable next steps
- Improve tracking plans, event quality, and attribution logic to ensure accurate and reliable measurement
- Write and optimize SQL queries and notebooks to support analysis
- Use AI assisted tools to support data exploration, query development, and analytical workflows
- Communicate data analysis results, insights, and recommendations clearly to stakeholders
- Collaborate with fellow analysts to review results, refine methodologies, and strengthen analytical approaches
Requirements
- Post-secondary education in Business, Economics, Mathematics, Data Science, Computer Science, or other related programs
- Experience in data analysis or product analysis
- Strong communication skills and ability to explain complex analysis clearly
- Solid understanding of statistics and experiment analysis
- Proficiency in SQL, including writing efficient queries with joins, aggregations, and filtering logic
- Knowledge of data mining and segmentation techniques
- Familiarity with Python for data analysis and visualization (ex. pandas, Matplotlib)
- Ability to manage multiple experiments and analyses simultaneously
- Experience analyzing and designing A/B experiments
- Proficiency using Microsoft Excel (Pivot Tables, Visualizations, Formulas) and Project Management software
- Ability to work independently and manage complex projects
- Strong interest in data analysis and a natural tendency to dig deeper into unexpected results.
Benefits
- Hybrid work arrangement
- Opportunities for a collaborative and inclusive learning culture
- Fast, easy to use, and professional solutions
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