Principal Data Analyst, Product
Cumbernauld, North Lanarkshire, G67, Scotland, UK
Listed on 2026-05-30
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IT/Tech
Data Analyst, Data Science Manager, Business Systems/ Tech Analyst
Ready to make travel easier for millions? Airalo is the world’s first and largest eSIM store, helping travellers stay connected seamlessly in over 200 countries and regions. We trust our teams to take ownership, put customers first, and do work that has a real impact every day. What’s in it for you? Airalo offers team members a range of perks, including remote work, generous PTO, wellness and learning allowances, and, of course, our annual Airalo Away retreat.
Hi, I'm Andra, Director of Data at Airalo!
Our team works across the full data ecosystem, from collection to insights activation, ensuring that every piece of data drives meaningful action. We’re curious problem-solvers who love tackling challenges that haven’t been solved before and building tools and processes that scale impact across the company.
Airalo’s fully remote Data team is growing. You’ll turn numbers into decisions that shape the future of our business, collaborating with cross-functional teams to solve complex problems and influence how millions of travellers stay connected. This isn’t just dashboards - it’s using data to drive strategy, inform product and growth decisions, and create real impact. You’ll have access to best-in-class tools, the freedom to experiment, and a team ready to turn insights into action.
We're looking for a Principal Data Analyst, Product to elevate product analytics 'll identify the questions the product org should be asking before they ask them, connect product metric movements to revenue, and build the analytical frameworks that product teams use to make better bets — frameworks that work when you're not in the room. You'll partner directly with product leadership and cross-functional stakeholders to shape product strategy through data, and help define how we scale coverage, structure the discipline, and raise the bar across squads.
WhatYou'll Do:
- Partner with Product teams to define success metrics, design experiments, and evaluate feature impact
- Design and analyse experiments with statistical rigour - hypothesis discipline, power analysis, pre-registered success metrics, and clear decision criteria.
- Evaluate our experimentation tooling landscape and determine what's fit for purpose.
- Define tracking plans, naming conventions, and instrumentation governance with engineering so we can measure feature impact before we ship.
- Define and implement product-level KPIs within our tiered framework, connecting product metrics to business outcomes.
- Build and maintain governed product dashboards in Light Dash, driving self-service adoption across product squads.
- Train PMs and product leaders to interpret funnel metrics, read experiment results, and use governed reporting with confidence.
- Conduct deep-dive analyses on user behaviour, funnel performance, cohort trends, and retention dynamics.
- Size opportunities and build business cases before the product team commits — connecting metric movements to revenue impact.
- Partner with product leadership to evaluate product bets, inform roadmap prioritisation, and deliver recommendations to leadership and the board.
- Partner with fractional squad analysts to elevate product analytics capability through coaching, review rituals, and shared frameworks.
- Help shape how product analytics scales at Airalo - coverage models, org design, and where to invest next.
- Partner with data and product engineering to define event tracking requirements and ensure product instrumentation meets analytical needs
- 7+ years in product analytics, data science, or quantitative analytics roles, with demonstrated impact at staff or principal 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.
- Proven experimentation expertise - you've built experimentation practices, not just run tests. You've introduced hypothesis discipline and decision frameworks to teams that didn't have them, and you know the common failure modes.
- Strong instrumentation and data governance instincts - you've defined tracking plans, worked with engineering on event taxonomy, and pushed…
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