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.
Build Airalo’s marketing measurement capabilities - owning the MMM, incrementality, and attribution portfolio while building and shaping the team that delivers it. This is a hands-on leadership role: in the first 6–12 months you’ll be roughly 50% hands-on (building models, running analyses, running experiments yourself) and 50% leading - setting technical direction, growing the team (2 then 3+ FTE), and partnering with senior stakeholders. As the team matures, the balance shifts toward leadership, but you’ll always stay close enough to the work to set the technical bar.
Responsibilities include, but are not limited to:
Build and shape the marketing and growth analytics pod as the function scales-set the technical standard and review bar for measurement work, define ways of working, and grow capability through direct coaching and mentorship.
Own the roadmap and prioritisation for the measurement portfolio, balancing reactive stakeholder demand against the longer-term decision-framework build—while staying hands-on enough to personally build, validate, and ship alongside the team.
Drive Airalo's growth MMM portfolio from validation into a production-grade decision tool, and scale to additional markets as growth ambition and data readiness allow.
Design and run incrementality experiments (geo-holdouts, lift studies, synthetic control, diff-in-diff) that calibrate the MMM and prove the causal impact of spend.
Evolve attribution methodology: the right models and windows for our purchase cycle, the data they require, and the signal quality that determines their accuracy
Own LTV:CAC as a strategic KPI reported to leadership: calculate and continuously optimize CAC across its variants (platform-reported, internally-attributed, incremental, blended), and turn MMM scenarios, incrementality results, and attribution insights into concrete budget changes.
Drive self-service enablement across Growth and Acquisition: build the reporting framework and tooling (alongside Analytics Engineering) that lets stakeholders answer their own questions, and raise measurement literacy so they can act with confidence.
Build institutional knowledge—document every experiment, MMM refresh, and signal-quality trend so each quarter's decisions are better informed than the last.
Operate as part of the wider data domain: partner with Analytics Engineering, Product and Business Analytics, Data Platform, Data Science, and MarTech to share standards and tooling, shape the signal infrastructure that underpins measurement, and contribute marketing measurement back into the org's shared foundation.
Must-haves:
Several years in marketing analytics, marketing science, or growth analytics, with deep, hands-on expertise in at least two of MMM (building/validating/calibrating, or close vendor partnership), incrementality testing (geo-experiments, RCTs), and multi-touch attribution.
Staff/Principal, Analytics Lead, or equivalent leadership-track experience (manager) - a hands-on leader who sets the technical bar and still ships, has led or mentored analysts/scientists, and is ready to build and grow a team from a small base.
Strong foundation in causal inference and experimental design difference-in-differences, synthetic control, propensity scoring, and when each applies.
A track record of owning channel-level CAC, LTV, churn, and ROAS, and using them to influence marketing spend at scale.
Strong SQL and Python (or R), comfortable writing production-quality code — on a modern warehouse (BigQuery or Snowflake), ideally with dbt/analytics-engineering workflows and a BI tool (LightDash, Looker Studio, Tableau, Metabase).
Exceptional communicator who navigates deep technical detail and translates it into clear recommendations for senior and board-level audiences.
Proactive self-starter who thrives in high-growth ambiguity.
Nice to haves:
- Experience building or scaling an analytics team or function in a high-growth environment.
- Experience with Bayesian modelling frameworks (TensorFlow Probability, PyMC, Stan) and their applications in marketing measurement.
- Familiarity with mobile analytics platforms and MMPs: Adjust, AppsFlyer, CleverTap, or similar.
- Experience with ad platforms (Google Ads, Meta Ads, TikTok Ads, Apple Search Ads) and their attribution APIs, conversion modelling, and server-side event integration (cAPI, Enhanced Conversions, SKAN).
- Knowledge of the eSIM, telco, MNO/MVNO, or travel-tech landscape.
- Exposure to semantic layers, metrics-as-code, or KPI governance frameworks.
- Experience with privacy-first measurement strategies in the post-cookie, post-ATT world.
- Experience with cross-border or multi-market attribution challenges where marketing geography and conversion geography diverge.
