Headout
Lead Data Analyst, Growth
Skills
2 months ago
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Important information
Contract type:
Permanent
Location:
Bengaluru, Karnataka, India
Work mode:
Onsite
Published on:
7 September 2026
What they need
👩 💻 The role
As Lead Analyst for Growth Data, you'll own the analytics function for Headout's growth teams and be the strategic partner to growth leadership. This isn't a reporting role; you'll shape how we measure, forecast, and accelerate Headout's acquisition and retention engine. You'll build the intelligence layer that transforms the team by building forecasting systems, dynamic pricing recommendations, and inventory health metrics that they’ll use to make decisions. You'll also mentor analysts, raise the bar on analytical rigor, and ensure insights are not just correct, but trusted and adopted.
We believe the best analysts own problems, not tasks. You'll be measured by the outcomes you enable, not the dashboards you ship.
🌟 What makes the role stand out?
- Shape Growth Intelligence, Not Just Reporting : You'll build systems that help Growth teams anticipate what's coming, not just measure what happened. Forecasting, pricing intelligence, inventory health; the foundations that turn reactive reporting into proactive decision-making.
- Strategic Partner : You'll partner with Growth leadership on strategy, not just answer their questions. Your analysis will influence how we allocate resources, prioritise markets, and place bets. This is a seat at the table.
- Global Scale, Real Complexity : Headout operates across 100+ cities with different supply mixes, seasonality patterns, and competitive dynamics. You'll decode what scales globally versus what needs local nuance, and build frameworks that work across markets, seasons, and channels.
🎯 What skills you need to have
- 4-7 years in data analytics, with significant time in growth, marketing, or product analytics in a consumer internet or B2C environment
- Deep understanding of growth mechanics: CAC/LTV, retention curves, funnel conversion, channel efficiency, and how they interact
- Advanced SQL and strong working knowledge of Python for analysis and automation.
- You've led analytics projects end-to-end: scoping, execution, storytelling, and driving adoption
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