Product Data Analyst

About the role

We're hiring a Product Data Analyst to be the analytical backbone of how we build, ship and improve our grant management platform. You'll partner directly with PMs, designers, and engineers to turn product usage data into decisions - what to build, what to kill, what to double down on. This is a high-leverage role: your dashboards, experiments and analyses will shape roadmap priorities and how thousands of foundations, nonprofits and grantmakers experience our product.

You'll own the full analytics lifecycle: instrumentation, modeling, exploration, reporting, and storytelling. You'll also be a key player in our shift toward AI-leveraged product development, helping us measure adoption and impact of new AI-powered features as they ship.

Location: Indore, India (on-site)

Responsibilities:

● Partner with Product Managers and designers on feature scoping - bringing data to should we build this and is what we built working

● Define and instrument product metrics (activation, engagement, retention, feature adoption) across web and API surfaces

● Build and maintain self-serve dashboards in our BI stack so PMs and execs can answer their own questions

● Design and analyze A/B tests, holdouts, and quasi-experiments; help the org be honest about what's signal vs. noise

● Run deep-dive analyses on user behavior: funnel drop-off, cohort retention, segment differences, JTBD validation

● Synthesize qualitative signal (Gong calls, Zendesk tickets, NPS) alongside quantitative data for a full picture of customer voice

● Contribute to our QBR cadence — own the metrics narrative for one or more product pillars

● Collaborate with data engineering on the warehouse data model (event schemas,

dimensional tables, semantic layer)

Must Haves:

● 6 + years in product analytics, growth analytics, or a similar analytical role at a SaaS or product-led company

● Strong SQL - comfortable writing complex queries against large event tables and warehouse models (BigQuery, Snowflake, Redshift, or similar)

● Hands-on experience with a product analytics tool (PostHog, Amplitude, Mixpanel, Heap)

● Solid grounding in experimentation: sample sizing, statistical significance, common pitfalls, when not to run a test

● Ability to translate fuzzy product questions into crisp analyses and write up findings clearly for non-technical stakeholders

● Comfortable with Python or R for analysis beyond what SQL can do

● Strong product intuition - you think like a PM, not just a query-writer

Nice to haves:

● Experience instrumenting and analyzing AI-powered product features (LLM agents, recommendation systems, automation)

● Familiarity with dbt, Looker, Metabase, or similar modeling/BI tooling

● Background in B2B SaaS, especially workflow software, CRM, or vertical SaaS

● Exposure to MongoDB or other document databases as a source system

● Experience working with qualitative research tools (Sprig, Maze, Dovetail)