
Sr. Data Analyst | Full-Time | Corporate
- New York City, NY Denver, CO
- $75,000-100,000 per year
- Permanent
- Full-time
- Data Analysis & Modeling
- Analyze complex data sets to develop and refine analytical frameworks and models that influence business strategies.
- Collaborate closely with business intelligence teams to transform raw data into actionable insights, enhancing operational efficiency and customer satisfaction.
- Reporting & Visualization
- Assist in the design and deployment of interactive dashboards and reporting solutions that provide real-time insights to stakeholders.
- Contribute to the development and maintenance of a centralized data dictionary or metric framework.
- Stakeholder Collaboration
- Support initiatives to integrate advanced analytics into daily operations, fostering a data-informed culture within the organization.
- Partner with venue teams to ensure alignment of KPIs and data definitions across the portfolio.
- Innovation & Partnership
- Contribute to managing external partnerships and vendor relations to expand data capabilities and technological advancements.
- Support ad hoc analysis requests across departments including marketing, operations, and finance.
- Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, or a related field, with 5+ years of data analytics experience.
- Proficiency with analytical tools (e.g., SQL, Python, R) and experience with BI platforms (e.g., PowerBI).
- Demonstrated ability to manage and analyze large data sets.
- Excellent problem-solving skills and the ability to communicate complex data in a clear and concise manner to non-technical stakeholders.
- Familiarity with collaboration tools (e.g., Jira, Planner, Confluence, or Slack).
- Experience in an Azure environment.
- Experience with Databricks.
- Skilled in statistical modeling, forecasting, and data mining techniques.
- Experience working with event, ticketing, F&B, or fan engagement data; Familiarity with sports, entertainment, or hospitality industry data.
- Experience with data governance, data quality, or data lineage.