The posting
Company description: Scandinavian Airlines System SAS Job description: Data Scientist Focused on Revenue Management & Network Optimization At SAS, we're passionate about transforming aviation with cutting-edge technology. As part of our ongoing Digital & IT transformation, we are expanding our investments in AI, machine learning, advanced analytics, and data-driven decision-making to create smarter customer experiences and stronger commercial performance. As part of our AI Team, you'll shape the future of air travel by creating innovative, data-driven solutions that maximize revenue. You will work on one of the most challenging and rewarding problems in the industry: finding the right price, for the right customer, at the right time. Your work will ensure that the airline's Revenue Optimization remains scientifically robust, operationally scalable, and commercially impactful, directly shaping how revenue is optimized in a dynamic, competitive marketplace. Your responsibilities will center on turning business challenges into well-defined analytical problems and building end-to-end machine learning solutions that deliver measurable impact. You will design, train, and maintain models that power SAS's revenue optimization, ensuring they are accurate, scalable, and production-ready. A priority will be to deliver dynamic pricing, a groundbreaking shift in how SAS competes in the marketplace. At the same time, we are developing AI-driven revenue optimization at scale, ensuring our models continuously learn, adapt, and evolve with industry dynamics. Your work will help SAS unlock the full potential of AI in airline revenue optimization, making smarter pricing and network decisions a reality today. Challenges You Will Work On Machine Learning & Optimization Techniques Build and deploy algorithms that power revenue and network decisions. Among other solutions, you'll develop demand forecasting, purchase probability, and revenue optimization models, leveraging a broad spectrum of AI methods. From classical ensemble methods to deep learning architectures and reinforcement learning frameworks, you'll select the most effective approach for each complex problem. Operations Research Beyond building models, you'll explore new formulations, test novel algorithms and findings that push the boundaries of airline revenue optimization. You will convert advanced research into production-ready optimization and modeling solutions, collaborating with the Operations Research team to embed novel algorithms into initiatives that deliver measurable business impact. MLOps Leverage end-to-end ML infrastructure to take models from research to production at scale. This includes designing reproducible training and inference pipelines, integrating CI/CD workflows for seamless deployment, and ensuring robust monitoring to detect drift and trigger automated retraining, keeping models stable and accurate in production.
To be successful we believe you have Master's Degree or higher with strong mathematics focus (Data Science, Statistics, Econometrics, Applied Mathematics, Optimization, Computer Science) or related field. At least 3 years of industry experience within the Data Science domain. Proven record of taking on loosely defined problems and translating them into practical applications. Strong mathematical background (e.g., linear algebra, calculus, statistics, optimization). More than 3 years' experience with Python, SQL and popular machine/deep learning libraries. Proficient with statistical and machine learning models (both supervised and unsupervised learning). Well-versed in cloud computing. Prior experience with Azure is a big plus.
We believe you share our passion for data and algorithms. You're self-driven, persistent, creative, and curious, with a strong passion for learning. You seek to understand both the big picture and the intricate details that make it up. Like us, you get excited by commercial opportunities and proactively strive to create business value. Additional information Apply by November 16, 2026. We review applications continuously and encourage you to apply early, as the position may be filled before the closing date. Please note that, due to GDPR regulations, we cannot accept applications via email. This is a full-time position (100%) based at our headquarters in Frösundavik, Solna, Stockholm. We value in-person collaboration, although flexible working arrangements may be available depending on team and business needs. As this role contributes to security-classified systems and business-critical capabilities, a background check will be conducted as part of the final stage of the recruitment process.
Please note that applications must be submitted through our careers site, as we are unable to process applications received by email.
