Sr. Data Analyst
| Company | Raymond James Financial |
|---|---|
| Location | St. Petersburg, FL, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Senior |
Requirements
- Data management and experience supporting a multi-channel investment management distribution network and marketing footprint.
- Development and design in Salesforce Financial Services & Sales Cloud, Marketing Cloud, Data Cloud, Client Experience Cloud, Tableau, and Tableau Prep.
- Familiarity with go-to-market marketing tools such as: Seismic, LinkedIn, Sitecore, On24.
- Business intelligence and data visualization, with a preference for Tableau.
- Construction of interactive views or complex dashboards.
- Proficiency in languages for data management, mining, and manipulation (e.g., SQL).
- Competence in other statistical, predictive analysis or programming languages (e.g., Python).
- Industry data sources and the ability to work with complex data sets to drive meaningful insights.
- Understanding of investment management sales, marketing, and products.
Responsibilities
- Develop a solid understanding of the business structure, internal and industry data sets, operational and technical design, and the strategic direction of the organization to craft solutions and pose pertinent questions.
- Define use cases, identify trends, and create data models to bolster client engagement and acquisition strategies across digital marketing and various distribution channels. Collaborate on executing data models through pilots, multiple testing methodologies, benchmarking, and continuous learning to support future data projects.
- Craft ‘data stories’ and convey findings to our business partners, including senior management. Effectively communicate various data research using data visualization, workflows, and storytelling techniques to make insights understandable and actionable. Develop communications and methods for delivering actionable data insights with measurable results.
- Advocate for a ‘data-driven’ culture and prioritize delivering value to the business by actively enhancing processes through collaboration with the team and business partners.
- Establish robust partnerships within the organization, consulting with business partners and subject matter experts to comprehend business needs and integrate data and analytics effectively. Apply data science capabilities to address issues, break down data silos, and connect disparate industry data sets.
- Continuous learning and education through Identifying new data science, mining and research tools, techniques, statistical analysis, and industry vendors.
Preferred Qualifications
- Five (5) years of data science, data modeling, or Tableau certification highly preferred.