Senior Data Analyst
Role Overview
The RA&S Analytics team partners with business, marketing, distribution, product, and technology teams to turn complex data into insights that improve marketing performance, advisor engagement, sales outcomes, and client experience.
The team is shifting toward scalable data products, automated measurement, and decision-ready insights.
The Senior Data Analyst leads analytics from defining business questions through data integration, analysis, visualization, and recommendations.
The role connects marketing, digital, prospect, client, advisor, and sales data to reveal journeys and performance opportunities.
Key Skills for This Role
Full Job Posting
Role overview
The RA&S Analytics team partners with business, marketing, distribution, product, and technology teams to turn complex data into insights that improve marketing performance, advisor engagement, sales outcomes, and client experience.
The team is shifting toward scalable data products, automated measurement, and decision-ready insights.
The Senior Data Analyst leads analytics from defining business questions through data integration, analysis, visualization, and recommendations.
The role connects marketing, digital, prospect, client, advisor, and sales data to reveal journeys and performance opportunities.
What you will do
- Support analytics from requirements and data gathering through analysis and presentations for RA&S marketing teams.
- Build decision-ready reports and dashboards that show performance drivers, trends, and recommended actions.
- Integrate campaign and digital analytics with back-end source data to understand end-to-end client journeys.
- Translate analytical findings into business insights and recommendations and present findings to stakeholders at multiple levels.
- Collaborate across RA&S and Data and Analytics to deliver trusted solutions, automate recurring work, and communicate with technical and non-technical audiences.
- Continue to grow capabilities through training, peers, and other learning sources.
Required qualifications
- Five or more years of data experience, including quantitative analysis, data manipulation, and analytical reporting.
- Complex SQL querying and integration of data across databases; expert Python/PySpark skills and flexibility to work with both.
- Experience with AWS SageMaker, Glue, and Lambda, plus Adobe Analytics.
- Experience with Tableau or QuickSight, or ability to learn these tools in the role.
- BSc in a statistical, mathematical, or technical field such as computer science.
- Strong concise written and oral communication, collaboration across projects, expectation management, and work documentation.
- Reliability Status Clearance is required before starting; satisfactory background checks are required.
Nice to have
- Experience in life insurance, wealth management, or another financial services area.
- Knowledge of predictive or prescriptive methods such as regression, decision trees, or deep learning; an MSc in a relevant field; or experience with unstructured data.
Work arrangement
- Sun Life describes itself as a hybrid organization, with flexibility to work both in the office and virtually according to business, client, and employee needs.
Compensation
- The posting lists a base salary range of 85,000 to 128,000 without specifying a pay period.
- Eligible employees may participate in incentive programs; payments are discretionary and subject to individual and company performance.
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