At a Glance
- Tasks: Drive innovation in engineering through data science, collaborating with cross-functional teams.
- Company: Join Jet2.com and Jet2holidays, a leading airline redefining travel experiences.
- Benefits: Enjoy hybrid working, annual pay reviews, and a generous profit share scheme.
- Why this job: Be part of a dynamic team making impactful decisions in aviation using cutting-edge data analytics.
- Qualifications: Experience in data science, strong Python skills, and a passion for continuous learning required.
- Other info: Opportunities for professional development and exposure to the latest industry trends.
The predicted salary is between 42000 - 84000 £ per year.
We’re seeking a Senior Data Scientist to join our Jet2 Data Science team, specifically to work with our Airline Engineering team based at Leeds Bradford International Airport. Our Senior Data Scientist will be responsible for the delivery of key initiatives capable of realising significant value, combining insights gained from multiple large data sources with the contextual understanding and experience of our colleagues across the business. This exciting new role focuses on driving innovation within our engineering and maintenance operations, playing a critical role in executing our engineering data and analytics strategy.
You’ll join an established and growing team of Data Science professionals and be based within Engineering Technologies, who are leveraging the use of data-driven insights and innovative technologies to optimise our Engineering & Maintenance operations. As our Senior Data Scientist, you’ll have access to a wide range of benefits including:
- Hybrid working (we’re in the office 2 days per week)
- Annual pay reviews
- Access to a generous discretionary profit share scheme
What You’ll Be Doing
You’ll be expected to work with cross-functional teams to identify areas where Data Science techniques can add significant value, collaborating with and enthusing our stakeholders. You will:
- Be embedded within the Engineering Technologies team, identifying and assessing opportunities for data-driven improvements in safety, efficiency, and cost management.
- Work within a pod of Data Science professionals to develop and implement predictive analytics, time-series forecasting, and natural language processing models, in use cases that include forecasting aircraft maintenance needs and optimising operations.
- Take responsibility for delivering initiatives, adopt our Data Science ways of working, be able to break down initiatives into measurable tasks, and report progress and issues blocking progress.
- Work with our data teams to design and implement data collection, processing, and analysis frameworks, ensuring data integrity and accuracy.
- Be skilled at storytelling, be able to explain solutions to stakeholders and recommend actions to take for the business to realise value from that in our operations.
- Be committed to your personal and professional development, staying up to date with the latest trends and technologies in data science and engineering analytics.
- Demonstrate awareness of and adherence to the appropriate regulatory and internal policy requirements.
What You’ll Have
You’ll have demonstrable experience in delivering data science initiatives, from rapid prototyping to show proof of value through into production, and can detail experience in data preprocessing, feature engineering, and model evaluation. You’ll have demonstrable application of realising operational value in a regulated industry would be highly preferable. You’ll be highly numerate with a statistical background, with strong expertise in Python essential. Exposure to ML Frameworks like Scikit Learn/TensorFlow/PyTorch would be beneficial. You’ll have a deep understanding of data analytics technologies and an eagerness to explore new tools and techniques. Strong SQL skills are a must, with exposure to Snowflake desirable, and the ability to create clear data visualisations essential. Experience with Palantir Foundry and its applications is desired but not essential. Familiarity with cloud platforms available for data science and storage would also be desirable. You’ll appreciate the importance of data governance and how to assess and enhance data quality. You’ll preferably be knowledgeable or be interested in aerospace/airline engineering and maintenance principles, but not required. You’ll show commitment to keeping your knowledge up to date through self-learning, and be supported with opportunities to complete courses, attend industry events, and obtain technical certifications.
Join us as we redefine travel experiences and create memories for millions of passengers. At Jet2.com and Jet2holidays, your potential has no limits. Apply today and let your career take flight!
Senior Data Scientist (Engineering Technologies) employer: Jet2.com and Jet2holidays
Contact Detail:
Jet2.com and Jet2holidays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Scientist (Engineering Technologies)
✨Tip Number 1
Familiarise yourself with the specific data science tools and technologies mentioned in the job description, such as Python, SQL, and ML frameworks like Scikit Learn or TensorFlow. Being able to discuss your experience with these tools during an interview will demonstrate your readiness for the role.
✨Tip Number 2
Showcase your ability to work collaboratively by preparing examples of past projects where you successfully worked with cross-functional teams. Highlight how you identified opportunities for data-driven improvements and the impact those initiatives had on the business.
✨Tip Number 3
Brush up on your storytelling skills, as the role requires explaining complex data solutions to stakeholders. Practice articulating your past projects in a way that clearly outlines the problem, your approach, and the value delivered to the organisation.
✨Tip Number 4
Stay updated on the latest trends in data science and engineering analytics. Mention any recent courses, certifications, or industry events you've attended in your discussions, as this shows your commitment to personal and professional development, which is highly valued in this role.
We think you need these skills to ace Senior Data Scientist (Engineering Technologies)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, particularly in areas like predictive analytics and model evaluation. Use specific examples that demonstrate your skills in Python, SQL, and any ML frameworks you've worked with.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Discuss how your background aligns with the responsibilities outlined in the job description, especially your experience in delivering data science initiatives in regulated industries.
Showcase Your Technical Skills: Be explicit about your technical skills in your application. Mention your proficiency in Python, SQL, and any experience with tools like Scikit Learn or TensorFlow. If you have experience with cloud platforms or data governance, make sure to include that as well.
Demonstrate Continuous Learning: Highlight any recent courses, certifications, or industry events you've attended related to data science and engineering analytics. This shows your commitment to personal and professional development, which is important for this role.
How to prepare for a job interview at Jet2.com and Jet2holidays
✨Showcase Your Technical Skills
Make sure to highlight your expertise in Python, SQL, and any ML frameworks you've worked with. Be prepared to discuss specific projects where you applied these skills, especially in data preprocessing and model evaluation.
✨Demonstrate Your Problem-Solving Ability
Prepare examples of how you've identified opportunities for data-driven improvements in previous roles. Discuss how you approached these challenges and the impact your solutions had on efficiency or cost management.
✨Communicate Effectively
Since storytelling is crucial for this role, practice explaining complex data science concepts in simple terms. Be ready to discuss how you would present your findings to stakeholders and recommend actionable insights.
✨Stay Updated on Industry Trends
Show your commitment to personal and professional development by discussing recent trends in data science and engineering analytics. Mention any courses or certifications you're pursuing to stay ahead in the field.