Senior Data Analyst

4 weeks ago


Bradenton, Florida, United States AEG Full time
About the Role

The Senior Data Analyst will be responsible for leading the design and implementation of analytics solutions as part of the Sales Operations Team.

This position provides data, analysis, insights, and recommendations in support of the company's fiercely data-driven decision-making culture in sales, marketing, and financial domains.

The Sr. Data Analyst is responsible for partnering cross-functionally across the organization to understand business goals, define questions, and methods for answering them.

Working closely with the data teams, this position makes use of multiple data sources, analysis tools, and statistical frameworks to construct analytical outputs, reporting, and dashboards in support of daily operations, new initiatives, and the development of sales and marketing strategies.

Key Responsibilities
  1. Help the Sales Ops. Team cultivate cross-functional partnerships across departments, bringing insights to every corner of our operation as part of a collaborative, collegial learning culture.
  2. Provide analytic leadership and guidance to other members of the Sales Ops. team, offering thoughtful and timely coaching and effective feedback.
  3. Grow, mentor, and manage analytics delivery of other Jr Analysts.
  4. Partner with leadership in Marketing, Sales, and Operations to solicit analytics business requirements and frame actionable questions.
  5. Partner with the data team to perform data processing, querying, and analysis to answer business questions and provide actionable insights.
  6. Use visualization tools to communicate stories with data, creating reporting, dashboards, KPI monitoring, and self-service tools to make data and insights available for stakeholders.
  7. Partner with data team to identify and address limitations in data sources, data quality, tooling, or performance bottlenecks in analytics delivery.
  8. Be the subject matter expert on the business process and information flows.
  9. Seek opportunities to perform 'data pioneering' for identifying new opportunities for analysis and insight generation while maintaining focus on reuse and repurposing of frameworks across domains.
Requirements
  • Experience and understanding of how modern analytics frameworks are constructed to define questions and answers using applied statistical methods.
  • Strong data process definition and refinement skills, with an instinctive understanding for identifying areas of opportunity or challenge and methods for providing a clear analysis.
  • Ability to construct models for forecasting and tracking business performance in support of sales, marketing, operations, or financial domains.
  • Familiarity with data analysis using R or Python.
  • Expertise composing complex SQL queries for relational databases.
  • Hands-on experience building custom visualizations using Tableau.
  • Experience with modern data warehouse tools like Snowflake, Big Query, or Redshift.
  • Experience leading cross-functionally in situations requiring collaboration, negotiation, and communication of complex analyses to non-technical or senior management audiences.
  • Experience working as a team player with other data scientists and engineers; always looking to make things better and easier for co-workers.
  • Excellent visual, verbal, and textual communication and presentation skills; extremely strong skills for using data to tell stories, especially counter-intuitive or controversial ones.
  • Highly self-motivated, self-directed, resourceful, and autonomous; capable of managing multiple simultaneous deliverables with proactive status updates and requests for support.
  • Strong problem-solving skills with the ability to pinpoint and resolve problematic issues quickly and efficiently.
  • Comfortable working in a fast-paced and dynamic environment.
  • Bachelor's or master's degree in a quantitative discipline (Mathematics or Social Science).
  • 5+ years' data analytics experience in a commercial or scientific setting.
  • Experience supporting critical analytics delivery in a fast-paced environment.
  • Experience working across functional, product, and engineering teams.
  • Experience using task management and collaboration software such as Jira and Confluence.
  • Experience with distributed version control and software development lifecycle methods.
  • Exposure to Agile Development or the Scrum project management methodology a plus.

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