Senior Data Analyst, Product and Business

We're looking for a Senior Data Analyst, Product and Business to elevate how we use data across product and business Airalo. You'll work as an analytics partner to both the product org and broader business teams, connect product metric movements to business and feature performance and build the analytical frameworks that teams use to make better bets. You'll partner directly with product leadership and cross-functional stakeholders to shape strategy through data, and help define how we scale coverage and embed data driven decision making across the business.

What You'll Do

• Partner with product teams to define success metrics, design experiments, and evaluate feature impact.
• Design and analyse experiments with statistical rigour, while helping teams build confident experimentation capabilities and champion best practice.
• Collaborate with engineering to identify key metrics and tracking data needs, enabling ownership and quality of product data.
• Partner with product and business teams to guide and implement product-level KPIs within our tiered framework, connecting product metrics to business outcomes.
• Conduct deep-dive analyses spanning product and broader business performance, e.g. funnel, retention, and cohort trends, alongside operational, CX, or commercial performance.
• Size opportunities and build business cases before the team commits, connecting metric movements to revenue impact.
• Build and maintain governed dashboards in LightDash, and support self-serve analytics adoption across mixed-function squads (product, engineering, CX, marketing).
• Work together with PMs, product leaders, and other squad stakeholders to interpret metrics, read experiment results, and use governed reporting with confidence.
• Partner with leadership to evaluate bets, inform roadmap prioritisation, and contribute to recommendations for leadership.

What You'll Bring

• 4+ years in product or commercial analytics, data science, or other quantitative analytics roles, with demonstrated impact at a senior level.
• Deep experience with product analytics in a B2C, marketplace, or transactional environment - you understand funnels, retention curves, user lifecycle, and how product metrics connect to revenue.
• Comfortable moving between product, operational and commercial data, and joining the dots analytically to tell a fuller performance story.
• Proven experimentation expertise - you are knowledgeable in A/B testing, have worked in partnership with product teams on experimentation best practices and are experienced on decision frameworks and common failure modes.
• Strong instrumentation and data governance instincts - you've defined tracking data, worked with engineering on event taxonomy, and understand the importance of high quality data.
• Track record of shaping and delivering metrics and analytical frameworks that fit the needs of the area you're working in, with strong cross-functional alignment.
• Proven ability to size opportunities and connect product analytics to financial outcomes.
• Strong SQL and Python/R proficiency - you write queries and build analyses yourself regularly.
• Experience with data visualisation and BI tools such as LightDash, Looker, Tableau, or similar.
• Excellent communication skills - you tailor your message to your audience and are focused on helping everyone understand analytical complexities.
• Comfortable operating with autonomy where not everything is well-defined, and bringing structure without waiting for permission.
• A proactive, self-starter mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced environments where the analytics discipline is still being established.
• Comfortable using AI tools to augment analytical work - you've integrated AI into your workflows for exploration, code generation, or insight acceleration, and you have a point of view on where it helps and where it doesn't.

Nice to have

• Experience in marketplace, telecom, travel, or subscription/usage-based businesses.
• Experience with experimentation tools, and causal inference methods beyond A/B testing.
• Experience with product analytics tools (Amplitude, Mixpanel, Firebase, or similar).
• Familiarity with dbt, LightDash, or similar semantic/BI layers.
• Experience working in cross-functional teams spanning product, commercial and operational disciplines.