DATA SCIENTIST

Scandinavian Airlines System (SAS); Solna kommun; In loco; SEK 900.000 - 1.300.000; Tempo pieno

Descrizione del lavoro

Scandinavian Airlines System SAS is seeking a Data Scientist focused on Revenue Management and Network Optimization to join our AI Team in Solna. You will design and productionize ML models that drive pricing and network decisions, delivering measurable impact on revenue and commercial performance.

You will work across forecasting, demand modeling, and optimization, building end-to-end solutions and maintaining pipelines in a production environment, with a strong emphasis on scalability and

Competenze

• Master's degree or higher in a math/CS field.
• 3+ years of industry experience in Data Science.
• Translate loosely defined problems into practical ML applications.
• Strong mathematical foundation (linear algebra, calculus, statistics, optimization).
• 3+ years of Python, SQL and ML libraries.
• Proficiency with supervised and unsupervised ML models.
• Experience with Azure cloud computing.

Mansioni

• Develop end-to-end ML solutions for revenue management and network optimization.
• Build and deploy models powering pricing and network decisions with measurable impact.
• Create production-ready pipelines and CI/CD workflows for ML deployments.
• Collaborate with Operations Research and business teams to embed algorithms into initiatives.

Conoscenze

Machine Learning

Optimization

Python

SQL

Deep Learning

Reinforcement Learning

Statistics

Cloud computing

Formazione

Master's degree or higher in a math/CS field

Strumenti

Azure

Descrizione del lavoro

Data scientist

Kommun: Solna

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

• 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.

19587 Solna

Solna Kommun