Key responsibilities
Product analytics — analyse product usage data to understand user behaviour, feature adoption, and usage patterns across SmartStream products; surface insights to product teams and leadership
Data-driven decision support — design and analyse A/B tests; help product managers frame questions the data can answer and translate findings into recommendations
Cross-team insight — work across product groups rather than embedded in one; identify patterns, prospects, and risks that are only visible at the organisation level
AI adoption analytics — help measure and grow the adoption of AI-assisted development workflows across engineering; build the metrics and feedback loops that support this transition
Reporting and communication — build dashboards, reports, and narratives that make data accessible to non-analysts; present findings to product, engineering, and leadership audiences
Engineering analytics (developing) — over time, extend into engineering flow and delivery data (e.g. Jellyfish) as a complement to product insight




Security tooling analytics (developing) — over time, contribute to analysis of security tooling adoption and effectiveness (e.g. Snyk coverage, remediation trends) as part of the wider engineering enablement picture

Skills & experience

Essential:
Comfortable working with data — SQL, Python with pandas, or equivalent
Solid written and verbal communication; able to explain findings clearly to non-technical audiences
Curious, self-directed, and comfortable working across teams rather than within one

Strongly preferred:
Some hands-on experience with product analytics tools (PostHog, Amplitude, Mixpanel, GA, or similar)

Developed in role:
Statistics and experiment design
Understanding of how agile product and engineering teams work and make decisions
Interest in AI and how it changes the way software is built
Exposure to security tooling and metrics

Growth path

The initial focus is product analytics

📌 Product Operations Specialist Mumbai
🏢 SmartStream
📍 Mumbai