Business Analyst - Live Events Experience
New
IndiaContract
Salary not disclosed
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Job Details
- Required Skills
- PythonSQLBusiness IntelligenceData AnalysisETLTableauPandasData visualization
Requirements
- Strong experience in business or data analysis focused on customer behavior, pricing strategy, or segmentation.
- Advanced proficiency in SQL, including joins, CTEs, and window functions across multiple data sources.
- Hands-on experience with BI and visualization tools such as Tableau, Domo, or similar platforms.
- Working knowledge of Python for data analysis, including pandas and data wrangling techniques.
- Experience working with transactional, ecommerce, or monetized datasets (orders, SKUs, pricing, items, etc.).
- Strong analytical thinking with the ability to work through ambiguous, messy, and incomplete datasets.
- Ability to communicate insights clearly to both technical and non-technical stakeholders.
- Experience building dashboards, reports, and structured analytical outputs for business decision-making.
- Familiarity with ETL concepts, data pipelines, and multi-system data environments.
- Strong problem-solving mindset with the ability to translate business questions into data solutions.
- Comfortable working in fast-paced environments with evolving priorities and requirements.
Responsibilities
- Analyze customer behavior across live event and festival ecosystems, including segmentation, purchasing patterns, pricing elasticity, and product performance.
- Provide data-driven recommendations on pricing and product strategy, answering key business questions around what to sell and at what price.
- Work with complex transactional datasets including tickets, food, beverages, merchandise, SKUs, and multi-channel orders.
- Build and maintain analytical workflows using SQL and Python to enable repeatable and scalable insights generation.
- Develop dashboards, reports, and visualizations to communicate insights clearly to business and technical stakeholders.
- Support festival and business unit leadership teams with actionable insights that influence P&L decisions.
- Navigate and analyze non-traditional consumption patterns, including annual or seasonal purchasing behavior models.
- Collaborate with cross-functional teams to ensure data consistency across multiple systems and sources.
- Translate business problems into structured analytical questions and deliver clear, decision-ready outputs.
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