Description
Company is the global leader in AI-driven sports content automation. The platform powers digital asset management, creation, and distribution for the NBA, NHL, ESPN, and dozens of other major leagues, broadcasters, and rights holders worldwide.
You will be the analytical owner of your product domains — turning data into decisions for Product, R&D, Operations, and Business teams. Day to day, you will work hands-on in SQL and BI tools, partner closely with PMs and engineers, and help shape the strategic direction of the product through evidence.
WHAT YOU'LL DO:
- Own all analytical aspects of your assigned product domains
- Build and maintain reports, dashboards, and metrics, and monitor the integrity and validity of the data behind them
- Use analytical tools, data mining, and business logic to consult the Product team on day-to-day questions and decisions
- Analyze and optimize products and activities, take part in design and implementation as a key voice in strategic product decisions
- Own and manage multiple data initiatives and projects, both ongoing and ad-hoc
- Define alerts and monitor performance to improve process efficiency
- Provide supporting data to help prioritize new features and initiatives
- Work closely with Product, R&D, Operations, and Business teams
Requirements
WHAT YOU'LL NEED:
- 4+ years in a Product / Data / Business / Operations Analyst role in a data-rich environment
- Current position MUST be an analyst role at a tech company (no finance, banking, or insurance backgrounds)
- Excellent SQL — daily, hands-on query writing. This is not a role where SQL is occasional; expect to live in it
- Strong verbal English (B2+ or higher). You will present findings to PMs, engineers, and business stakeholders directly in English every week.
- Proven experience using AI tools in your analytics workflow (e.g. ChatGPT, Claude, Gemini, or similar for query generation, data exploration, or summarization)
NICE TO HAVE:
- Hands-on experience with Tableau, Power BI, or Looker
- Experience analyzing datasets via an LLM tool
- Passion for sports
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