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(Only 24h Left) Product Analyst

(Only 24h Left) Product Analyst

LivspaceIndia
12 hours ago
Job description

About Livspace

Livspace is Asia’s largest and fastest-growing omni-channel home interiors and renovation

platform. We are building the future of Home Tech—a domain that merges design,

technology, and e-commerce to transform how people experience home interiors. With

exciting opportunities to expand into home technology and tech-enabled interiors, this is

the place to be if you want to make a visible impact in a high-growth industry.

About the Role

We are seeking a Product Analyst to join our Product team at Livspace. The ideal candidate

is data-driven, detail-oriented, and passionate about solving business and product problems

with numbers. You will partner with Product Managers, Engineers, and Designers to

analyze product usage, track KPIs, and deliver insights that shape our strategy in the Home

Tech and Interiors domain.

Key Responsibilities

  • Partner with Product Managers to define, track, and measure product success metrics.
  • Analyze customer behavior, funnels, and cohorts to identify opportunities for growth, engagement, and retention.
  • Build dashboards and reports using SQL and visualization tools (QuickSight, Tableau,etc.).
  • Conduct deep-dive analyses and generate actionable insights to inform product decisions.
  • Design and evaluate A / B tests to validate hypotheses and measure impact.
  • Collaborate with cross-functional teams (Product, Tech, Marketing, Ops) to enable data-backed decision-making.

Requirements

  • 3–5 years of total experience, with at least 2 years as a Product Analyst (preferably in e-commerce or consumer internet companies).
  • Strong analytical skills with proficiency in : SQL (mandatory), Excel / Google Sheets for quick analysis, Data visualization tools such as QuickSight, Tableau, Power BI, Looker, or equivalent.
  • Familiarity with product analytics tools (e.g., Amplitude, Mixpanel, GA, Clevertap).
  • Knowledge of A / B testing design and evaluation.
  • Ability to simplify complex datasets into clear, actionable recommendations.
  • Strong communication and presentation skills.
  • Degree in Engineering, Statistics, Mathematics, Economics, or related field preferred.
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