Background in live events, entertainment, hospitality, or seasonal business models
Strong experience in data analysis with a focus on consumer behavior, customer segmentation, or pricing strategy
Proficiency in SQL for querying and transforming large datasets
Experience with BI/dashboarding tools (Domo, Tableau, or similar)
Requirements:
Analyze consumer behavior across festival properties: customer segmentation, purchasing patterns, pricing elasticity, and product assortment effectiveness
Answer strategic questions around Price (what should we charge and why) and Product (what should we sell and why)
Work with transactional data (tickets, food, beverages, merchandise) across orders, carts, items, assortments, SKUs, and pricing
Support each festival's PL leadership with data-driven insights and recommendations
Job description
Role: Business Analyst - Live Events Experience Position Type: Full-Time Contract (40hrs/week) Contract Duration: 6+ months Work Schedule: 8 hours/day (Mon-Fri) Location: 100% Remote - Candidates can work from anywhere in India)
Preferred Qualifications:
Background in live events, entertainment, hospitality, or seasonal business models
Experience with pricing analytics, A/B testing, or marketing effectiveness analysis
Familiarity with ETL processes and data pipeline concepts
Experience working with multiple POS systems or disparate data sources that require reconciliation
Responsibilities:
Analyze consumer behavior across festival properties: customer segmentation, purchasing patterns, pricing elasticity, and product assortment effectiveness
Answer strategic questions around Price (what should we charge and why) and Product (what should we sell and why)
Work with transactional data (tickets, food, beverages, merchandise) across orders, carts, items, assortments, SKUs, and pricing
Navigate the unique "once a year " purchasing cycle of festival data vs. traditional ecommerce recency/frequency models
Support each festival's P&L leadership with data-driven insights and recommendations
Build and maintain analytical workflows using SQL and Python for repeatable analysis
Represent findings clearly through charts, slides, or dashboards to support business decision-making
Required Qualifications:
Strong experience in data analysis with a focus on consumer behavior, customer segmentation, or pricing strategy
Proficiency in SQL for querying and transforming large datasets (CTEs, window functions, joins across multiple data sources)
Experience with BI/dashboarding tools (Domo, Tableau, or similar)
Working knowledge of Python for analytical scripting (pandas, data wrangling, statistical analysis)
Experience with transactional/ecommerce data (orders, items, pricing, SKUs) or similar monetarily-driven datasets
Ability to clearly communicate analytical findings to both technical and business stakeholders
Comfort working with ambiguity: messy data, multiple systems, incomplete information
Can clearly communicate ideas both technical and business teams
Notes:
Strong Business Analysis
Strong Analytical thinking
Experience working with data (SQL, dashboards, etc.)
Ability to:
Translate business problems → data questions
Communicate insights clearly
Comfortable with SQL, BI tools, building pipelines and deep engineering work
