Analyst, Digital Data, Global Wealth Management

In this role you will:

• Partner with Global Wealth Management product, digital, and advisor platform teams to enable data driven decision making
• Define and execute analytics strategy and roadmap aligned to GWM digital analytics priorities, including digital footprint across all platforms
• Measure and analyze performance of wealth digital experiences (e.g., advisor portals, client-facing digital platforms, onboarding and servicing flows)
• Identify opportunities to improve client experience and advice quality and increase advisor effectiveness and adoption of digital tools
• Deliver analytics solutions and data products that support client segmentation and personalization, advisor insights and decision support and lifecycle and journey optimization
• Collaborate with data scientists, data engineers, and platform teams to automate trusted data pipelines and reporting, implement data quality, controls, and monitoring, and ensure analytics solutions are scalable and compliant
• Communicate insights clearly and effectively to Wealth business leaders, digital partners, and senior stakeholders, translating complex analyses into actionable recommendations
• Support experimentation (A/B testing, pilots, proofs of value) to validate hypotheses and measure business impact in regulated wealth environments

• 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 solid 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, Num Py, 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