Head of Product Analytics & Experimentation

Qlub; Riyadh; On-site; SAR 180,000 - 280,000; Full time

Job summary

Qlub is seeking a leader to head product analytics, building the experimentation engine to scale to 50 AB tests a month and defining the data model and semantic layer for reliable analytics and AI.

You will coach a small team of analysts, establish governance with Tech and Data Engineering, and partner with Product, Operations, and Growth to bring an AI-first analytics approach to a fast-moving fintech.

Qualifications

• 5+ years in analytics or data science at a large data-driven company or modern data platform.
• Hands-on experimentation programme development with power analysis, variance reduction, sequential testing.
• Strong data modelling: dimensional modelling, SCDs, event schema design, dbt, SQL.
• Track record of driving change and getting non-technical teams to adopt new practices.
• Clear communication with executives and non-technical stakeholders.

Responsibilities

• Own end-to-end experimentation; set design standards, sample sizing, metrics, guardrails, and review results.
• Train PMs and operations leads to run sound experiments; build playbooks, templates, and review rituals.
• Define analytical data model, entity and event design across product flows; semantic layer and metrics.
• Introduce data contracts and governance with Tech & Data Engineering for correct event/table design.
• Coach and grow a team of three junior analysts and one senior analyst.
• Communicate clearly with executives and non-technical stakeholders.

Skills

Experimentation

Statistics

Power analysis

Variance reduction

Sequential testing

Data modelling

SQL

Communication

Leadership

Tools

dbt

Airflow

Git

BigQuery

ClickHouse

Google Cloud Storage

Job description

The role

You ll lead product analytics at qlub and build the experimentation engine behind our growth scaling to 50 A B tests a month You ll set the standard for how our data is modelled so analytics and AI can trust it and lead a team of BI analysts working closely with Product Operations Tech and Data Engineering

What you ll own

• Own experimentation end to end configure and scale our existing A B testing platform set standards for test design sample sizing metrics and guardrails and review results
• Train product managers and operations leads to run sound experiments themselves and build the playbooks templates and review rituals that make this routine
• Define the analytical data model entity and event design that joins consistently across product flows slowly changing dimensions a semantic layer and metric definitions
• Introduce data contracts and governance standards with Tech and Data Engineering so that new events and tables are designed correctly from the start
• Coach and grow a team of three junior analysts and one senior analyst

Who you are

You ve built and scaled an experimentation culture and you re rigorous on test design while pragmatic about when evidence is enough to decide You love teaching turning PMs and ops leads into confident experimenters and growing analysts through direct kind coaching You think in systems and care about data models definitions and governance because reliable analytics and AI depend on them You drive change through influence and clear reasoning partnering well across Product Operations Tech and Data Engineering You communicate clearly with executives and non-technical stakeholders and you re excited to bring an AI-first approach to analytics in a fast-moving global fintech

What you ll need

• 5 years in analytics or data science including time at a large data-driven company e g Delivery Hero Uber Amazon Meta Booking or a modern data or experimentation platform e g Sigma Mixpanel Amplitude Statsig Optimizely
• Hands-on experience building or scaling an experimentation programme with solid statistics power analysis variance reduction sequential testing and common pitfalls
• Strong data modelling dimensional modelling SCDs event schema design dbt and SQL at a high level
• A track record of driving change introducing new practices into organisations and getting non-technical teams to adopt them
• Clear communication with executives and with non-technical stakeholders

Nice to have

• Data science and predictive modelling including forecasting
• Experience building an AI-first data stack and taking an AI-first approach to analytical problems
• Data governance frameworks marketing analytics and attribution
• Experience with tools and technologies such as dbt Airflow Git Google Cloud Storage GCS BigQuery or ClickHouse
• Familiarity with data governance and cataloguing tools such as Atlan Alation or OpenMetadata

Who you are

You've built and scaled an experimentation culture, and you're rigorous on test design while pragmatic about when evidence is enough to decide. You love teaching, turning PMs and ops leads into confident experimenters and growing analysts through direct, kind coaching. You think in systems and care about data models, definitions and governance, because reliable analytics and AI depend on them. You drive change through influence and clear reasoning, partnering well across Product, Operations, Tech and Data Engineering. You communicate clearly with executives and non-technical stakeholders, and you're excited to bring an AI-first approach to analytics in a fast-moving, global fintech.

What you ll need

5+ years in analytics or data science, including time at a large data-driven company (e.g. Delivery Hero, Uber, Amazon, Meta, Booking) or a modern data or experimentation platform (e.g. Sigma, Mixpanel, Amplitude, Statsig, Optimizely). Hands-on experience building or scaling an experimentation programme, with solid statistics: power analysis, variance reduction, sequential testing, and common pitfalls. Strong data modelling: dimensional modelling, SCDs, event schema design, dbt, and SQL at a high level. A track record of driving change: introducing new practices into organisations and getting non-technical teams to adopt them. Clear communication with executives and with non-technical stakeholders.