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, opportunities, 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
- Strong 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, where SmartStream has a explicit unmet need, alongside supporting the organisation's AI-assisted development transition through data. Over time, the role can grow into broader engineering enablement — engineering metrics (Jellyfish), security tooling insight, and cross-cutting analysis of how the organisation delivers software. A strong platform for a career in analytics, engineering effectiveness, or data-informed product leadership.

📌 Product Operations Specialist (Mumbai)
🏢 Smartstream
📍 Mumbai