出海雷达

Staff Data Scientist, Pricing

其他限定地区(需当地身份)日间重叠约 2 小时,需偶尔早起或晚睡
公司Airalo
薪资£93,200 - £139,800/年
工作地点Spain, United Kingdom
地域资格限定地区(需当地身份)
时区要求日间重叠约 2 小时,需偶尔早起或晚睡
用工类型Full Time
发布时间今天
数据来源Himalayas
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注意地域限制:该职位明确限定在 Spain、United Kingdom 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。
作息提示:日间重叠约 2 小时,需偶尔早起或晚睡。
关于本页中文:职位描述由本机离线模型翻译,属机器翻译,供快速判断用;正式沟通与投递请以英文原文为准。官方翻译通道恢复后会自动重译升级。

帮助我们建立旅游的未来 在 Airalo,我们让人们在任何地方都更容易保持联系。作为世界上第一家 eSIM 商店,我们帮助数百万旅客访问全球200多个国家和地区的负担得起的移动数据。今天,我们是一个由60多个国家的400+人组成的团队,每天构建出旅行者使用的产品。我们迅速发展,但我们努力维护重要的事情:信任,所有权和人们免费做好伟大的工作的自由。我们是设计完全远程,真正全球化,并被一个共同使命所统一,使旅游变得更加简单。你的下一步目的地 · 地点:远程共享。· 合同:全职,永久。· 优势:在这里了解更多我们的好处 - · 语言:英语是我们日常工作的主要语言,所以你需要在会议和无机交互中感到舒服。我们正在寻找一个数据科学家,定价人员来建立分析和机器学习能力,从需求建模到推价格的系统。你不会从零开始。我们已经投资了基本数据和基础设施,定价决策取决于这些信息。缺少的是顶部的能力:商业信任的模型,以证据解决价格问题的实验和一旦定义的经济学,使它们在商业,产品和客户体验中保持一致。角色从测量到预测到处方 - - 理解需求如何对价格作出反应,预测它将如何响应,最终构建推价格本身的模型。你会做什么:·建立并拥有需求和弹性模式能力,定量价格如何影响目的地,持续时间,数据层次和客户部门中的容量。· 开发对需求预测和付费愿意的机器学习模型,从探索到生产,并通过监控和重训来保持诚实。· 将我们从预测到规范性转化为优化的层,使预测和弹性成为在边际,竞争力和合作伙伴限制下推价格。· 用统计严格设计和分析定价实验,并在清洁随机化不可能的情况下应用因果方法。· 在我们的数据生态系统中定义定价,拥有管理的定义:

查看英文原文

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

  • Location: Remote.
  • Contract: Full-time, permanent.
  • Benefits: Learn more about our benefits here in this link -
  • 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:

  • Build and own the demand and elasticity modelling capability, quantifying how price affects volume across destination, duration, data tier, and customer segment.
  • 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.
  • 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.
  • Design and analyse pricing experiments with statistical rigour, and apply causal methods where clean randomisation isn't possible.
  • 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.
  • Partner with Commercial and Finance to connect pricing decisions to margin and revenue, and to size opportunities before we commit.
  • 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:

  • 7+ years in data science, quantitative economics, or applied research, including pricing, monetisation, or marketplace economics work that demonstrably changed decisions.
  • Experience with dynamic or algorithmic pricing systems in production.
  • 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.
  • Hands-on machine learning experience across the full lifecycle, from feature engineering and model selection through to deployment
  • Familiarity with optimisation and decision-science methods that turn predictions into recommended actions, whether through constrained optimisation, bandits, or reinforcement learning approaches.
  • Proven experimentation expertise, having designed and defended experiments with a clear view on decision frameworks and common failure modes.
  • Experience building analytical capability where none existed before, turning raw data and a business question into something a commercial team uses repeatedly.
  • Strong data modelling instincts, thinking in reusable definitions and single sources of truth rather than standalone analyses.
  • The ability to move comfortably between financial, product and operational data and connect the analysis to a financial outcome.
  • Genuine partnership instincts, translating between analytical rigour and commercial reality so that Commercial and Product come to you early rather than after the decision.
  • Fluency in the Python ML stack alongside strong SQL, with the engineering hygiene to hand over code that others can run and maintain.
  • Excellent communication skills, including the ability to make a methodological argument to people who won't check your standard errors.
  • A self-starter mindset that thrives in ambiguity and brings structure without waiting for permission.
  • Comfort using AI tools to augment analytical work, with a point of view on where they help and where they don't

Nice to have:

  • Experience in marketplace, telecom, travel, or subscription/usage-based businesses.
  • Bayesian or hierarchical modelling for sparse segments and long-tail SKUs.
  • Competitive price response modelling, or working with scraped competitor pricing data.
  • Familiarity with dbt, LightDash, or similar semantic/BI layers.
  • Experience designing semantic or metric layers consumed by both analytics and production systems.
  • Experience working in cross-functional teams spanning commercial, finance and product disciplines.

If you are interested in this position, please apply via the link.
Why People Join Us
We started Airalo to make staying connected effortless, wherever you are in the world. Today, millions of travelers rely on our eSIMs, and many of the people building the product were customers first.
Our team spans 60+ countries, united by a shared belief that great work happens when people are trusted to own what they do. There's trust to own what you do, space to focus without constant layers of process, and a clear sense of what you're responsible for from day one.
As Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact - from anywhere in the world.
Before You Hit Apply
By applying, you acknowledge and agree that, in case of successful application, Airalo may request to run background checks as a condition for entering into an agreement with you. Rest assured that these checks will only occur upon your prior consent and at the end of the selection process, and will be strictly limited to what is allowed under the laws that are applicable to you. All data that you share or that we collect in connection with such checks will be processed in accordance with our Privacy Policy, available here:
We sincerely thank all applicants in advance for submitting their interest in this opportunity. Airalo is an equal-opportunity employer and values diversity, equity & inclusion. We do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We are committed to providing reasonable accommodations upon request for individuals with disabilities throughout our job interview process.
Originally posted on Himalayas

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