Growth Analyst| Info Edge | Bangalore|

Info Edge Limited; Bengaluru; On-site; INR 400,000 - 650,000; Full time

Job summary

Info Edge Limited in Bengaluru is seeking a data/growth analytics professional to own and automate analyses across paid acquisition, funnel, and retention.

You will build dashboards for leadership, run A/B tests, and translate insights into actionable recommendations, leveraging SQL, Python, and LLM tools.

Qualifications

• 2-3 years in data or growth analytics.
• Advanced SQL with joins and window functions.
• CTEs on large event tables.
• Python with pandas, including automating recurring analyses.
• Working knowledge of growth metrics: CAC, ROAS, LTV, cohort retention, funnel conversion.
• Stats basics: significance testing, sample sizing.
• Ability to turn analysis into clear recommendations for non-analysts.
• Comfort using LLM tools to speed up querying and analysis.

Responsibilities

• Analyse paid acquisition performance on Meta and Google by campaign.
• Run funnel and cohort analyses across install to paid conversion.
• Build LTV and payback views by channel and cohort.
• Design A/B tests and incrementality studies; write clear readouts.
• Measure lifecycle performance.
• Own daily and monthly growth reporting and dashboards for leadership.
• Automate recurring analyses to save time for decision-making.

Skills

Advanced SQL

Window functions

CTEs on large tables

Python (pandas)

Growth metrics

Cohort retention

Funnel conversion

A/B testing

LLM tools

Data storytelling

Job description

• Analyse paid acquisition performance on Meta and Google: CAC, CPA, ROAS by campaign, creative and audience
• Run funnel and cohort analysis from install to signup, approval and paid conversion, with D1/D7/D30 retention
• Build LTV and payback views by channel and cohort to guide budget allocation
• Design A/B tests and incrementality studies, and write clear readouts
• Measure lifecycle performance
• Own daily and monthly growth reporting and dashboards for leadership Automate recurring analyses so the team spends time on decisions, not data pulls

• 2-3 years in data or growth analytics Advanced SQL: joins, window functions,
• CTEs on large event tables Python with pandas, including automating recurring analyses
• Working knowledge of growth metrics: CAC, ROAS, LTV, cohort retention, funnel conversion Stats basics: significance testing, sample sizing, and common pitfalls in cohort comparisons
• Ability to turn analysis into a clear recommendation for non-analysts Comfort using LLM tools to speed up querying and analysis