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About the role
Minimum of 3-5 years of progressive experience in data analysis, sales and marketing analytics, financial modeling, or data mining, with a strong focus on extracting actionable insights from large datasets.
Experience in digital banking, marketing, or credit risk is a significant asset.
Post-Secondary education or equivalent experience in a quantitative field such as Statistics, Mathematics, Computer Science/Engineering, Operations Research, Economics, or Business Administration, coupled with a solid understanding of data analytics principles.
Expert in SQL for querying large, complex datasets (BigQuery Standard SQL is a plus).
Demonstrated experience with statistical software (e.g., SAS, R, Python) and/or programming/scripting languages.
Hands-on experience building and deploying machine learning models for customer segmentation, propensity modeling, and personalization.
Hands-on experience with digital analytics platforms (e.g., Google Analytics, Adobe Analytics) and media platforms (e.g., Google Marketing Platforms, Facebook) Proficiency in developing reports and interactive dashboards using BI tools (e.g., Tableau, Looker).
Strong understanding of database structures and schemas.
Advanced MS Office skills (Excel, PowerPoint).
Exceptional analytical, problem-solving, and critical thinking skills with the ability to synthesize complex information into clear, actionable recommendations.
Solid understanding of digital marketing and eCommerce best practices.
Proven ability to communicate complex analytical findings and strategic insights effectively, both verbally and in written presentations, to diverse technical and non-technical audiences.
Strong organizational skills and attention to detail, ensuring accuracy and quality in all deliverables.
Ability to manage multiple complex projects, prioritize effectively, and deliver high-quality results in a dynamic, fast-paced environment.
Demonstrated personal accountability and a results-oriented approach.
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