Product Analytics Lead

Moontech

About The Position

This is a role for a senior analyst who can operate inside a live infrastructure buildout, help get the data foundation right, and use AI tools to work faster than a traditional analyst stack allows. This person turns event data, campaign performance, and growth metrics into decisions the product and leadership team can act on immediately. The role reports to the CPO and sits inside the product organization, not a shared analytics function, so priorities follow the roadmap. The individual will work closely with the data and engineering team on infrastructure work, and with the PM team on instrumentation and metrics.

Requirements

5+ years in product analytics or data analysis, ideally at a marketplace, e-commerce, or performance-marketing company.
Experience partnering directly with PMs and engineers on instrumentation, not just consuming finished data.
Comfortable working with imperfect data and evolving schemas.
Hands-on experience with a customer data platform or event tracking pipeline and a modern BI or dashboarding tool.
Fluent in SQL and comfortable in Python, at minimum pandas, for anything a dashboard tool cannot do.
AI-native by practice, not just interest. You use LLMs and agents daily to write queries, generate analysis code, summarize data, or automate reporting, and can speak concretely about how that has changed your output, not just that you are interested in AI.
Strong written and verbal communication. You turn analysis into a clear recommendation, not just a chart.

Nice To Haves

Growth-stage startup experience is a strong plus.
A track record owning north-star and funnel or retention metrics for a two-sided or marketplace product.
Background in influencer, affiliate, or performance-marketing analytics.
GCC or MENA market experience.
Experience configuring agentic analytics workflows, beyond prompting a chat interface.

Responsibilities

Define, track, and report north-star and funnel metrics for both brands and creators, including signup, activation, early campaign performance, retention, and payouts.
Partner with PMs to define event tracking specs as part of feature planning, not as a follow-up request to engineering after launch.
Work directly with the data and engineering team on our ongoing data infrastructure modernization.
Validate data quality, flag gaps, and act as a product-side partner on schema and taxonomy decisions.
Build and maintain dashboards so PMs, leadership, and investors can get answers without waiting on ad hoc requests.
Tie product and campaign changes to revenue, retention, and unit economics.
Help design A/B tests, size samples, read out results, and maintain an experiment log.
Bring UAE and GCC context, including trust, timing, creative refresh, and short attention windows, into how funnel and campaign data gets interpreted.
Contribute clean, defensible numbers to board and investor updates.
Support data literacy across the PM team as part of a broader push toward analytics discipline.