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At Airalo, we're making it easier for people to stay connected wherever they travel. As the world's first eSIM store, we help millions of travelers access affordable mobile data in 200+ countries and regions around the world.
Today, we're a team of 400+ people across 60+ countries, building a product used by travelers every day. We've grown quickly, but we've worked hard to keep what matters: trust, ownership, and the freedom for people to do great work without unnecessary layers or bureaucracy.
We're fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone.
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:
You'll no longer be considered for this role and your application will be removed from the employer's inbox.