About the role
structured by ORIThe Vice President, Client Engagement Analytics within Wealth Management is responsible for setting and executing the analytics strategy that enables data-driven decisions for the Financial Planning team within Morgan Stanley’s Client Segments division. This role partners closely with Financial Planning strategy…
What you will do
- Serve as a trusted, central point of contact for senior stakeholders within Financial Planning; own the Financial Planning analytics and data strategy across Wealth Management, ensuring analytics priorities align to strategic goals and measurable outcomes.
- Define and drive the roadmap to unify planning activity data and client/advisor insights across platforms (e.g., planning tools, CRM, dashboards) by framing business questions and translating them into rigorous analytical approaches.
- Establish a scalable analytics model that enables timely, data-driven insights through a consistent, connected view of operational data and reporting.
- Own delivery of core performance reporting and benchmarks (e.g., leadership insights, KPIs, dashboards, recurring business reviews), ensuring quality, consistency, and an executive-ready narrative.
- Partner with business SMEs and technology partners to standardize core KPI definitions, integrate disparate data sources, and develop dynamic data assets for analytics and downstream consumption.
What they are looking for
- Bachelor’s degree in a quantitative or business discipline (e.g., Statistics, Economics, Data Science, Computer Science, Engineering); Master’s degree preferred.
- 7+ years of analytics experience in financial services (preferably wealth management) and 3–5+ years leading teams and/or large cross-functional analytics programs.
- Strong proficiency in SQL and Python, including 5+ years of hands-on data analysis and insight generation; demonstrated experience defining analytical approaches and applying a range of analytical tools to synthesize insights.
- Extensive business intelligence experience, including reporting and process automation, data visualization tools (Tableau), and big data platforms such as Dataiku, Snowflake, Hadoop, and Salesforce.
- Strong technical and analytical skills with the ability to manipulate large datasets and distill them into clear conclusions and actionable recommendations.
- High accuracy and analytical rigor; strong attention to detail and sense of ownership given the high-visibility nature of deliverables.
- Demonstrated ability to work independently and solve problems creatively, including maintaini
Nice to have
- Master’s degree preferred.
Full posting text
The Vice President, Client Engagement Analytics within Wealth Management is responsible for setting and executing the analytics strategy that enables data-driven decisions for the Financial Planning team within Morgan Stanley’s Client Segments division. This role partners closely with Financial Planning strategy leadership as well as technology, sales, and risk/compliance, to deliver trusted metrics, scalable reporting, and advanced analytics. This is a business-facing, strategic analytics role for a hands-on, data-driven leader who can translate ambiguity into clear analytical approaches, actionable insights, and measurable outcomes. You will build the analytics infrastructure for Financial Planning, with a focus on uncovering opportunities to deepen client engagement and improve financial planning efficacy and effectiveness. Success in this role requires autonomy, strong curiosity about data, and the ability to deliver timely solutions that drive business results. The ideal candidate brings an AI- and automation-first mindset — advancing the use of AI tools and processes is considered table stakes — along with demonstrated people leadership and the ability to scale support efficiently, including effective partnership with offshore teams. Key Responsibilities * Serve as a trusted, central point of contact for senior stakeholders within Financial Planning; own the Financial Planning analytics and data strategy across Wealth Management, ensuring analytics priorities align to strategic goals and measurable outcomes. * Define and drive the roadmap to unify planning activity data and client/advisor insights across platforms (e.g., planning tools, CRM, dashboards) by framing business questions and translating them into rigorous analytical approaches. * Establish a scalable analytics model that enables timely, data-driven insights through a consistent, connected view of operational data and reporting. * Own delivery of core performance reporting and benchmarks (e.g., leadership insights, KPIs, dashboards, recurring business reviews), ensuring quality, consistency, and an executive-ready narrative. * Partner with business SMEs and technology partners to standardize core KPI definitions, integrate disparate data sources, and develop dynamic data assets for analytics and downstream consumption. * Partner with technology teams to ensure analytics-ready data models and pipelines are built efficiently; identify gaps in data availability and drive resolution. * Lead, mentor, and develop a high-performing analytics team and offshore resources by setting clear priorities and standards for deliverables, with a strong focus on quality, timeliness, and scale. * Partner with Legal/Compliance/Operational Risk to implement and evidence appropriate governance for data access and reporting distribution. Qualifications * Bachelor’s degree in a quantitative or business discipline (e.g., Statistics, Economics, Data Science, Computer Science, Engineering); Master’s degree preferred. * 7+ years of analytics experience in financial services (preferably wealth management) and 3–5+ years leading teams and/or large cross-functional analytics programs. * Strong proficiency in SQL and Python, including 5+ years of hands-on data analysis and insight generation; demonstrated experience defining analytical approaches and applying a range of analytical tools to synthesize insights. * Extensive business intelligence experience, including reporting and process automation, data visualization tools (Tableau), and big data platforms such as Dataiku, Snowflake, Hadoop, and Salesforce. * Strong technical and analytical skills with the ability to manipulate large datasets and distill them into clear conclusions and actionable recommendations. * High accuracy and analytical rigor; strong attention to detail and sense of ownership given the high-visibility nature of deliverables. * Demonstrated ability to work independently and solve problems creatively, including maintaini