Principal Data Analyst (Marketing Analytics)

Requirements

• Do you thrive at the intersection of marketing science and business strategy?
• This role is for someone who combines deep technical expertise with the ability to influence how a global organisation thinks about growth
• If you're ready to operate at the frontier of modern marketing measurement in a high-growth, global business - we'd love to hear from you
• Several years of experience in marketing analytics, marketing science, or growth analytics, with deep expertise across at least two of Marketing Mix Modeling, Incrementality Testing (geo-experiments, RCTs), and Multi-Touch Attribution
• Hands-on experience building, validating, or calibrating MMM models- whether using Robyn, Google Meridian, Py MC-Marketing, Lightweight MMM, Bayesian regression, or working closely with vendors who do
• Strong foundation in causal inference and experimental design: you understand difference-in-differences, synthetic control, propensity scoring, and when each method is appropriate
• Expert-level SQL and Python (or R). You can write production-quality code, not just analysis notebooks
• Experience with modern data warehouses (Big Query or Snowflake) and familiarity with analytics engineering workflows (dbt preferred)
• Experience with data visualisation and BI tools such as Light Dash, Looker Studio, Tableau, or Metabase
• Proven track record of calculating and optimising channel-level CAC, LTV, churn, and ROAS, and using these metrics to influence marketing spend decisions at scale
• Exceptional communicator: you navigate deep technical conversations and translate findings into clear recommendations for senior stakeholders and board-level audiences
• A proactive, self-starter mindset. You thrive in ambiguity, work autonomously, and are energised by building in fast-paced, high-growth environments
• (Desirable) Experience with Bayesian modelling frameworks (Tensor Flow Probability, Py MC, Stan) and their applications in marketing measurement
• (Desirable) Familiarity with mobile analytics platforms and MMPs: Adjust, Apps Flyer, Clever Tap, or similar
• (Desirable) Experience with ad platforms (Google Ads, Meta Ads, Tik Tok Ads, Apple Search Ads) and their attribution APIs, conversion modelling, and server-side event integration (c API, Enhanced Conversions, SKAN)
• (Desirable) Knowledge of the e SIM, telco, MNO/MVNO, or travel-tech landscape
• (Desirable) Exposure to semantic layers, metrics-as-code, or KPI governance frameworks
• (Desirable) Experience with privacy-first measurement strategies in the post-cookie, post-ATT world
• (Desirable) Experience with cross-border or multi-market attribution challenges where marketing geography and conversion geography diverge
• What the job involves
• 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, Marketing Analytics to own and execute our marketing measurement strategy - from Marketing Mix Modeling and incrementality testing through to attribution, channel economics, and budget allocation
• You'll design experiments, build models, and deliver the insights that shape how we invest our marketing spend across 190+ countries
• But measurement only matters if it changes decisions - so you'll also drive adoption of your work across the Growth organisation, build measurement literacy with stakeholders, and elevate the data culture that turns analysis into action
• Manage and evolve Airalo’s growth MMM portfolio - driving the existing market model from validation into a production-grade decision tool, and scaling to additional markets as growth ambition and data readiness allow
• Design and execute incrementality experiments (geo-holdouts, conversion lift studies, synthetic control, difference-in-differences) that calibrate the MMM and establish true causal impact of marketing spend across channels
• Evolve our attribution methodology: determine the right models and attribution windows for our purchase cycle, specify the data requirements, and measure the impact of tracking remediation on attribution accuracy
• Calculate and continuously optimize the CAC metrics (platform-reported, internally-attributed, incremental, and blended) and own LTV: CAC as a strategic KPI reported to leadership
• Build measurement literacy within the Growth and Acquisition teams: train stakeholders to interpret the LTV/CAC related metrics, understand the difference between attributed and incremental performance, and use self-service reporting with confidence
• Build and maintain the performance marketing reporting framework - with Analytics Engineering to ensure the underlying models serve both reporting and measurement needs
• Act as analytics partner to the Growth and Acquisition teams: translate business questions into measurement plans, deliver the analytics that inform spend decisions, and build self-service reporting that reduces ad-hoc dependency
• Drive adoption of measurement outputs-ensure MMM scenarios, incrementality results, and attribution insights translate into concrete budget allocation changes
• Contribute to the development of a unified decision framework that integrates signal health, attribution, and incrementality into budget allocation guidance with clear go/no-go criteria for scaling spend by market and channel
• Build institutional knowledge: document every experiment result, every MMM refresh, and every signal quality trend so that each quarter’s decisions are better informed than the last
• Collaborate with the Senior CDP Engineer and Mar Tech on the data and signal infrastructure that underpins measurement - defining what you need, so they can build it right
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