Senior Product Analyst

Location: Bangalore (Hybrid).

Notice Period: Immediate Joiners (upto 15 days).

About us:

Zemoso is an AI-native product engineering company helping Fortune 500 companies and high-growth enterprises turn complex ideas into production.

We work with enterprise teams to build production-grade AI agents for real business workflows, driving measurable outcomes and ROI.

We also help engineering organizations modernize how software is built, applying AI across the SDLC to move from idea to production faster.

Zemoso has contributed to over $10 billion in value creation across healthcare, financial services, logistics, biotech, retail, and e-commerce.

We are a 3x Deloitte Fast 50 company and an O'Reilly Architectural Katas winner.

Our technology partnerships include Anthropic, Databricks, Google Cloud and AWS.

Role overview:

We are hiring a Senior Product Analyst with 5+ years of experience in product analytics, experimentation and causal inference to join our team in Bangalore.

You will turn ambiguous product questions into rigorous analytical frameworks, partner with Product, Design, and Engineering to define KPIs, and influence product roadmaps with data-driven insights.

What You will do:

• Play the role of Senior Product Analyst, acting as the primary analytics thought partner to Product, Engineering, and Science teams within cross-functional pod structures.

• Scope ambiguous product questions with stakeholders, define North Star metrics, establish success and guardrail metrics, and deliver unbiased findings that directly inform roadmap decisions.

• Design and execute A/B experiments end-to-end: define target audiences, determine traffic sizing, execute power analysis, implement variance reduction (CUPED), manage multiple-comparison corrections, and monitor metrics post-launch.

• Guide experiment tracking setup by defining event action requirements, dropping proper experiment tags (XT tags), and validating telemetry pipelines before data analysis begins.

• Apply causal inference techniques and Quasi-Experimental Alternatives to measure feature impact where randomized controlled trials (RCTs) are unfeasible or unethical.

• Perform deep-dive product analytics - including multi-step funnel optimization, cohort tracking, and retention analysis - to pinpoint drop-offs and drive feature prioritization.

• Lead strategic analysis beyond standard experiment readouts, including quarterly strategy planning, opportunity sizing, and metric deep dives to uncover customer needs.