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- Tasks: Join easyJet as a Commercial Data Scientist, tackling data-driven challenges in pricing and scheduling.
- Company: easyJet connects over 90 million passengers annually with a focus on low-cost travel and friendly service.
- Benefits: Enjoy a hybrid work model, collaborative team culture, and opportunities for personal growth.
- Why this job: Make a real impact in the aviation industry while working with innovative data solutions and a supportive team.
- Qualifications: Ideal candidates have a background in data science, mathematics, or economics, with some industry experience preferred.
- Other info: Work closely with various teams and contribute to exciting projects in a dynamic environment.
The predicted salary is between 36000 - 60000 £ per year.
Description
Commercial Data Scientist
Luton/Hybrid
The Team
The Commercial departments in easyJet are responsible for allocating, scheduling, pricing and providing inflight services for more than 100 million passengers across the network annually. As a Data Scientist in the Commercial function, you will play a key role in supporting and developing data-driven solutions that enhance strategic decision-making across pricing, revenue management, network & scheduling planning, and inflight retail teams.
You\’ll bring a foundation in data science and a passion for solving commercial challenges through data, algorithms, and experimentation. This role is ideal for candidates with some industry experience or strong academic exposure who are ready to take more ownership and contribute meaningfully to impactful projects.
You will report to the Senior Commercial Data Science Manager. This role is ideal for someone with a strong background in mathematical modelling, statistics, economics, or optimisation who if eager to tackle high-impact, system-level decisions in the aviation industry.
You will:
Collaborate with senior/lead data scientists, analysts, and business stakeholders to scope and define high-impact problems.
• Conduct in-depth data analysis to identify trends and opportunities in booking patterns, route performance, pricing elasticity, and customer segments.
• Build, validate, and deploy predictive and optimisation models in Python and SQL for use in either pricing, forecasting, route/network performance, or operational optimisation.
• Design and support A/B tests and data experiments to measure the impact of commercial initiatives.
• Work with Data Engineers, MLOps Engineers and BI teams to integrate models into production pipelines and dashboards.
• Collaborate with Network and Scheduling Planning, Operations, Trading and Revenue Management, Inflight Retail, and IT teams to gather requirements and translate business problems into solvable mathematical models.
• Communicate findings and recommendations clearly, both in technical detail and at a business level.
• Contribute to the improvement of internal tools and codebases used across the Commercial Data Science team.
Requirements of the Role
What You\’ll Need:
• Collaborate with senior/lead data scientists, analysts, and business stakeholders to scope and define high-impact problems.
• Conduct in-depth data analysis to identify trends and opportunities in booking patterns, route performance, pricing elasticity, and customer segments.
• Build, validate, and deploy predictive and optimisation models in Python and SQL for use in either pricing, forecasting, route/network performance, or operational optimisation.
• Design and support A/B tests and data experiments to measure the impact of commercial initiatives.
• Work with Data Engineers, MLOps Engineers and BI teams to integrate models into production pipelines and dashboards.
• Collaborate with Network and Scheduling Planning, Operations, Trading and Revenue Management, Inflight Retail, and IT teams to gather requirements and translate business problems into solvable mathematical models.
• Communicate findings and recommendations clearly, both in technical detail and at a business level.
• Contribute to the improvement of internal tools and codebases used across the Commercial Data Science team.
Desirable experience
• Exposure to pricing, network optimisation, or demand forecasting problems.
• Experience with data visualisation tools (e.g., Power BI, Tableau).
• Familiarity with version control (Git), cloud platforms (GCP, AWS, or Azure), or orchestration tools (Airflow).
• Experience working in or with aviation, travel, retail, or transportation industries .
Experience working in Agile product teams or similar collaborative environments
These are full-time positions and we typically get together 2-3 times a week.
About easyJet
At easyJet our aim is to make low-cost travel easy – connecting people to what they value using Europe\’s best airline network, great value fares, and friendly service.
It takes a real team effort to carry over 90 million passengers a year across 35 countries. Whether you\’re working as part of our front-line operations or in our corporate functions, you\’ll find people that are positive, inclusive, ready to take on a challenge, and that have your back. We call that our \’Orange Spirit\’, and we hope you\’ll share that too.
Apply
Complete your application on our careers site.
We encourage individuality, empower our people to seize the initiative, and never stop learning. We see people first and foremost for their performance and potential and we are committed to building a diverse and inclusive organisation that supports the needs of all. As such we will make reasonable adjustments at interview through to employment for our candidates.
JOB FAMILY M&P
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Commercial Data Scientist employer: Easyjet
Contact Detail:
Easyjet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Commercial Data Scientist
✨Tip Number 1
Familiarise yourself with the aviation industry, especially in areas like pricing and demand forecasting. Understanding the specific challenges faced by easyJet will help you tailor your discussions during interviews.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are crucial for building and deploying predictive models. Consider working on personal projects or contributing to open-source projects to showcase your abilities.
✨Tip Number 3
Network with professionals in the data science and aviation sectors. Attend relevant meetups or webinars to connect with potential colleagues and gain insights into the role and company culture at easyJet.
✨Tip Number 4
Prepare to discuss your experience with A/B testing and data visualisation tools. Being able to articulate how you've used these methods in past projects will demonstrate your practical knowledge and problem-solving skills.
We think you need these skills to ace Commercial Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in areas like mathematical modelling, statistics, and optimisation. Use keywords from the job description to demonstrate your fit for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data-driven solutions and how your background aligns with easyJet's commercial challenges. Mention specific projects or experiences that showcase your skills in Python, SQL, and data analysis.
Showcase Relevant Projects: If you have worked on projects involving predictive modelling, A/B testing, or data visualisation, be sure to include these in your application. Provide brief descriptions of the projects and the impact they had.
Prepare for Technical Questions: Anticipate technical questions related to data science methodologies and tools. Brush up on your knowledge of Python, SQL, and any data visualisation tools you’ve used, as well as your understanding of pricing and demand forecasting.
How to prepare for a job interview at Easyjet
✨Showcase Your Data Skills
Be prepared to discuss your experience with data analysis, predictive modelling, and optimisation techniques. Highlight specific projects where you've successfully applied Python and SQL to solve real-world problems.
✨Understand the Commercial Landscape
Familiarise yourself with easyJet's business model and the aviation industry. Be ready to discuss how data science can impact pricing strategies, revenue management, and customer segmentation in this context.
✨Prepare for Technical Questions
Expect questions that test your knowledge of mathematical modelling, statistics, and A/B testing. Brush up on these concepts and be ready to explain them clearly, as you may need to demonstrate your thought process during the interview.
✨Communicate Effectively
Practice explaining complex data findings in simple terms. You’ll need to convey your insights to both technical and non-technical stakeholders, so focus on clarity and relevance in your communication.