The Company, a USA Subsidiary is a rapidly growing, private equity-backed SaaS company founded by engineers, focused on building scalable, high-quality products. Our solutions support over 3000 organizations, enabling them to manage grants, scholarships and philanthropic initiatives effectively. We offer cloud-based platforms that power the end-to-end lifecycle of grants, scholarships, fellowships, employee giving, and volunteer programs. In our organization, we foster a collaborative, innovation-driven culture with a flexible work environment and competitive benefits.
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 :
5 + 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)
How you'll be measured
Quality and timeliness of analyses that inform shipped product decisions
Health of the metrics stack: trust, freshness, coverage, self-serve adoption
Velocity and rigor of the experimentation program
Cross-functional reputation as a thought partner, not a ticket-taker
How we will take care of you:
Great working environment
Rapid career development opportunities
