Data Analyst

Vivid Seats•Chicago, IL

12d•$60,000 - $75,000•Hybrid

About The Position

Vivid Seats is hiring a Data Analyst II for its investments team, a small, fast-paced team that uses data to support ticketing partnerships, pricing decisions, and inventory strategy across the live events business. The role offers autonomy and early ownership of projects, with manager guidance and broad exposure to ticket pricing, inventory management, and the dashboards and models used to support business decisions. The analyst will work with a small team to identify pricing and inventory opportunities, forecast demand, and surface risks using data and market signals. Work may focus more heavily on pricing depending on the analyst’s strengths and interests. The role includes building and maintaining dashboards, reports, and analytical tools; analyzing large datasets and market conditions; automating recurring analyses; and communicating findings to stakeholders. The analyst will support and eventually lead small analytical projects from defining the question through presenting findings. Vivid Seats operates on a hybrid schedule, with employees expected to work in the Chicago office three days per week. Full-time offers include annual bonus incentives, FLEX PTO, mental health days, medical, dental, and vision insurance, 401(k) matching, quarterly credits and discounts for attending live events, and additional workplace perks.

Requirements

Bachelor's degree in a quantitative field such as statistics, mathematics, computer science, economics, or a similar field.
1–2 years of experience in a data analyst, business intelligence, or related analytical role; internship experience may count.
Proficiency in SQL and comfort writing and optimizing queries against large datasets.
Working knowledge of Python for data analysis and automation.
Experience building dashboards and reports in a business intelligence tool.
Ability to work with imperfect or messy data and reconcile data quality issues.
Strong communication skills and ability to translate data into clear takeaways for non-technical stakeholders.

Nice To Haves

Experience with Snowflake.
Experience with Looker.

Responsibilities

Build and maintain dashboards, reports, and analytical tools using platforms such as Looker, Python, and Excel to provide visibility into pricing, inventory, and program performance.
Build predictive models and analytical tools to identify pricing and inventory opportunities based on expected outcomes and changing market conditions.
Write and optimize SQL queries against Snowflake to pull, join, and analyze large datasets, using AI-assisted tools where appropriate.
Use Python to automate recurring analyses and streamline data workflows.
Analyze historical sales, marketplace supply, event characteristics, and external signals such as team performance, betting or prediction markets, and weather to identify pricing opportunities and downside risk.
Partner with team members to improve pricing, inventory performance, and operational efficiency.
Support and eventually lead small analytical projects end-to-end, from framing the question to presenting findings.
Contribute approaches, methods, or technologies that support business goals and improve team efficiency.
Maintain and support internal and external relationships to advance objectives.