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A University degree in Business, Finance, or a relevant STEM discipline (Computer Science, Engineering, Mathematics, Statistics) or equivalent practical experience
Hands-on experience with data analysis, performance measurement, and stakeholder engagement
A strong ability to simplify and communicate complex analytical insights to business and executive audiences
Experience or strong familiarity with Wealth Management concepts, such as product and client journeys, products and client segmentation and regulatory and compliance considerations is an asset
A proven ability to clean, transform, and analyze large datasets across multiple formats (e.g., structured, semi-structured, logs, JSON, flat files)
Proficiency in SQL and at least one analytical/programming language (Python or R preferred)
Working knowledge of data science and analytics libraries (e.g., Pandas, NumPy, scikit learn, Git)
Experience working with big data or cloud-based analytics platforms and building large, performant queries
Experience with data visualization tools such as Power BI, Tableau, or Qlik
A familiarity with digital analytics or behavioral data tools (e.g., Adobe Analytics, Google Analytics, Splunk) applied to digital wealth platforms
A foundational understanding of analytical techniques including descriptive and diagnostic analytics, predictive modeling and segmentation and time series and trend analysis
Strong project management and collaboration skills
Excellent written and verbal communication skills
The ability to manage multiple initiatives and priorities in parallel
Strong attention to detail and data accuracy
A comfort working both independently and collaboratively
An analytical, structured, and solution oriented mindset
Analyst, Digital Data, Global Wealth Management
Toronto, ONPosted 1 weeks ago