Staff Data Scientist, Pricing
Help Us Build The Future of Travel
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.
Your Next Destination
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Location: Remote.
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Contract: Full-time, permanent.
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Benefits: Learn more about our benefits here in this link -
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Languages: English is our main working language day to day, so you'll need to be comfortable communicating in it both in meetings and async.
We're looking for a Staff Data Scientist, Pricing to build the analytical and machine learning capability that pricing runs on, from demand modelling through to the systems that recommend price.
You won't be starting from zero. We've invested in the foundational data and infrastructure that pricing decisions depend on. What's missing is the capability on top: models the business trusts, experiments that settle pricing questions with evidence, and economics defined once so they hold consistently across Commercial, Product and the customer experience.
The arc of the role runs from measurement to prediction to prescription - understanding how demand responds to price, forecasting how it will respond, and ultimately building the models that recommend the price itself.
What You'll Do:
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Build and own the demand and elasticity modelling capability, quantifying how price affects volume across destination, duration, data tier, and customer segment.
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Develop machine learning models for demand forecasting and willingness-to-pay, and take them from exploration through to production with the monitoring and retraining that keeps them honest.
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Move us from predictive to prescriptive by building the optimisation layer that turns forecasts and elasticities into recommended prices under margin, competitive and partner constraints.
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Design and analyse pricing experiments with statistical rigour, and apply causal methods where clean randomisation isn't possible.
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Define pricing within our data ecosystem, owning the governed definitions of price, cost and package economics that reporting, analysis and product surfaces all read from.
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Partner with Commercial and Finance to connect pricing decisions to margin and revenue, and to size opportunities before we commit.
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Set the analytical standard for pricing at Airalo , from what counts as evidence through to how a model or recommendation gets validated before it influences live pricing.
What You'll Bring:
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7+ years in data science, quantitative economics, or applied research, including pricing, monetisation, or marketplace economics work that demonstrably changed decisions.
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Experience with dynamic or algorithmic pricing systems in production.
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An advanced degree in Econometrics, Statistics, Operations Research or similar, or equivalent applied depth in demand estimation and the identification problems that make naive price-quantity regressions wrong.
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Hands-on machine learning experience across the full lifecycle, from feature engineering and model selection through to deployment
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Familiarity with optimisation and decision-science methods that turn predictions into recommended actions, whether through constrained optimisation, bandits, or reinforcement learning approaches.
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Proven experimentation expertise, having designed and defended experiments with a clear view on decision frameworks and common failure modes.
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Experience building analytical capability where none existed before, turning raw data and a business questi