{"id":72516,"title":"Staff Data Scientist, Pricing","company":"Airalo","city":null,"region":null,"location":"Germany","work_model":"remote","employment_type":"full_time","employment":["full_time"],"roles":["data_science"],"visa":"not_mentioned","relocation":"not_mentioned","posted_at":"2026-08-18T07:53:55.606000+00:00","tools":["Python","SQL","dbt"],"seniority":"lead","years_experience_min":null,"german_requirement":"not_mentioned","german_level":"unspecified","english_requirement":"required","english_level":"unspecified","team_language":"unknown","confidence":0.4,"method":"rules","language_badge":"Not stated","language_evidence":null,"requirements_snippet":"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 …","url":"https://jobs.lever.co/airalo/dd4643aa-12f5-47fe-a30c-741f4e8d03df","source":"lever","agency":null,"description_text":"Help Us Build The Future of Travel\nAt 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.\nToday, 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.\nWe're fully remote by design, genuinely global, and united by a shared mission to make travel simpler for everyone.\nYour Next Destination\nLocation: Remote.\nContract: Full-time, permanent.\nBenefits: Learn more about our benefits here in this link - https://airalo-public.notion.site/Benefits-25396a97ffca81fb9bc1f0be479f1be3?pvs=74 \nLanguages: English is our main working language day to day, so you'll need to be comfortable communicating in it both in meetings and async.\n \n\n\nWe'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.\nYou 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.\nThe 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.\n\nWhat You'll Do:\n•\nBuild and own the demand and elasticity modelling capability, quantifying how price affects volume across destination, duration, data tier, and customer segment.\n\n•\nDevelop 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.\n\n•\nMove us from predictive to prescriptive by building the optimisation layer that turns forecasts and elasticities into recommended prices under margin, competitive and partner constraints.\n\n•\nDesign and analyse pricing experiments with statistical rigour, and apply causal methods where clean randomisation isn't possible.\n\n•\nDefine pricing within our data ecosystem, owning the governed definitions of price, cost and package economics that reporting, analysis and product surfaces all read from.\n\n•\nPartner with Commercial and Finance to connect pricing decisions to margin and revenue, and to size opportunities before we commit.\n\n•\nSet 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.\n\nWhat You'll Bring:\n•\n7+ years in data science, quantitative economics, or applied research, including pricing, monetisation, or marketplace economics work that demonstrably changed decisions.\n\n•\nExperience with dynamic or algorithmic pricing systems in production.\n\n•\nAn 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.\n\n•\nHands-on machine learning experience across the full lifecycle, from feature engineering and model selection through to deployment\n\n•\nFamiliarity with optimisation and decision-science methods that turn predictions into recommended actions, whether through constrained optimisation, bandits, or reinforcement learning approaches.\n\n•\nProven experimentation expertise, having designed and defended experiments with a clear view on decision frameworks and common failure modes.\n\n•\nExperience building analytical capability where none existed before, turning raw data and a business question into something a commercial team uses repeatedly.\n\n•\nStrong data modelling instincts, thinking in reusable definitions and single sources of truth rather than standalone analyses.\n\n•\nThe ability to move comfortably between financial, product and operational data and connect the analysis to a financial outcome.\n\n•\nGenuine partnership instincts, translating between analytical rigour and commercial reality so that Commercial and Product come to you early rather than after the decision.\n\n•\nFluency in the Python ML stack alongside strong SQL, with the engineering hygiene to hand over code that others can run and maintain.\n\n•\nExcellent communication skills, including the ability to make a methodological argument to people who won't check your standard errors.\n\n•\nA self-starter mindset that thrives in ambiguity and brings structure without waiting for permission.\n\n•\nComfort using AI tools to augment analytical work, with a point of view on where they help and where they don't\n\nNice to have:\n•\nExperience in marketplace, telecom, travel, or subscription/usage-based businesses.\n\n•\nBayesian or hierarchical modelling for sparse segments and long-tail SKUs.\n\n•\nCompetitive price response modelling, or working with scraped competitor pricing data.\n\n•\nFamiliarity with dbt, LightDash, or similar semantic/BI layers.\n\n•\nExperience designing semantic or metric layers consumed by both analytics and production systems.\n\n•\nExperience working in cross-functional teams spanning commercial, finance and product disciplines.\n\nIf you are interested in this position, please apply via the link.\n\n\nWhy People Join Us\nWe 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.\nOur 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.\nAs Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact - from anywhere in the world.\nBefore You Hit Apply\nBy 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: www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy \n \nWe 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.","responsibilities_text":"•\nBuild and own the demand and elasticity modelling capability, quantifying how price affects volume across destination, duration, data tier, and customer segment.\n•\nDevelop 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.\n•\nMove us from predictive to prescriptive by building the optimisation layer that turns forecasts and elasticities into recommended prices under margin, competitive and partner constraints.\n•\nDesign and analyse pricing experiments with statistical rigour, and apply causal methods where clean randomisation isn't possible.\n•\nDefine pricing within our data ecosystem, owning the governed definitions of price, cost and package economics that reporting, analysis and product surfaces all read from.\n•\nPartner with Commercial and Finance to connect pricing decisions to margin and revenue, and to size opportunities before we commit.\n•\nSet 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.","requirements_text":"•\n7+ years in data science, quantitative economics, or applied research, including pricing, monetisation, or marketplace economics work that demonstrably changed decisions.\n•\nExperience with dynamic or algorithmic pricing systems in production.\n•\nAn 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.\n•\nHands-on machine learning experience across the full lifecycle, from feature engineering and model selection through to deployment\n•\nFamiliarity with optimisation and decision-science methods that turn predictions into recommended actions, whether through constrained optimisation, bandits, or reinforcement learning approaches.\n•\nProven experimentation expertise, having designed and defended experiments with a clear view on decision frameworks and common failure modes.\n•\nExperience building analytical capability where none existed before, turning raw data and a business question into something a commercial team uses repeatedly.\n•\nStrong data modelling instincts, thinking in reusable definitions and single sources of truth rather than standalone analyses.\n•\nThe ability to move comfortably between financial, product and operational data and connect the analysis to a financial outcome.\n•\nGenuine partnership instincts, translating between analytical rigour and commercial reality so that Commercial and Product come to you early rather than after the decision.\n•\nFluency in the Python ML stack alongside strong SQL, with the engineering hygiene to hand over code that others can run and maintain.\n•\nExcellent communication skills, including the ability to make a methodological argument to people who won't check your standard errors.\n•\nA self-starter mindset that thrives in ambiguity and brings structure without waiting for permission.\n•\nComfort using AI tools to augment analytical work, with a point of view on where they help and where they don't\n•\nExperience in marketplace, telecom, travel, or subscription/usage-based businesses.\n•\nBayesian or hierarchical modelling for sparse segments and long-tail SKUs.\n•\nCompetitive price response modelling, or working with scraped competitor pricing data.\n•\nFamiliarity with dbt, LightDash, or similar semantic/BI layers.\n•\nExperience designing semantic or metric layers consumed by both analytics and production systems.\n•\nExperience working in cross-functional teams spanning commercial, finance and product disciplines.\nIf you are interested in this position, please apply via the link.\nWhy People Join Us\nWe 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.\nOur 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.\nAs Airalo continues to grow, so do the opportunities to learn, take on new challenges, and make a real impact - from anywhere in the world.\nBefore You Hit Apply\nBy 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: www.airalo.com/more-info/privacy-policy?srsltid=AfmBOooBT0rXAj1FaNelZ3VfN0wvhwzvAoxdtHnOKSVETpiSjiXVuycy\nWe 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.","status":"open","duplicate_of":null,"first_seen":"2026-11-02T21:25:19.239040+00:00","responsibilities_summary":null,"requirements_summary":null,"all_tools":["Python","SQL","dbt"],"posting_language":"en","evidence":[{"language":"english","requirement":"required","quote":"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.","source":"rules"}],"years_experience_max":null,"mobility_evidence":[],"model_version":"rules-8","english_badge":"English required","company_id":324}