At a Glance
- Tasks: Lead data science initiatives and solve real-world problems in aviation analytics.
- Company: Join a forward-thinking company at the forefront of aviation technology.
- Benefits: Enjoy competitive pay, flexible working options, and a supportive learning environment.
- Other info: Opportunity to mentor others and grow your career in a dynamic field.
- Why this job: Make a significant impact by shaping best practices in advanced analytics and machine learning.
- Qualifications: Expertise in data science, machine learning, and collaboration across teams.
The predicted salary is between 60000 - 80000 £ per year.
About the Role
As a Principal Data Scientist, you will be a senior individual contributor who brings deep technical expertise while shaping best practices across the data science community. You will work closely with partners across product, engineering, and the business to design and deliver data‑driven solutions. This role combines technical leadership, collaboration, and hands‑on development to solve complex, real‑world problems in aviation analytics.
Responsibilities
- Act as a technical authority for advanced analytics, machine learning, and generative AI, defining and evolving best practices for scalable and robust solutions
- Provide thought leadership on emerging technologies and methodologies relevant to aviation analytics
- Mentor and coach data scientists, supporting continuous learning and technical excellence
- Collaborate with product managers, engineers, and domain experts to align data science initiatives with business goals
- Translate complex technical insights into clear, actionable recommendations for stakeholders
- Lead by example through hands‑on coding, modelling, and solution design
- Design, prototype, and validate innovative approaches to high‑impact problems
- Partner with engineering teams to deploy models into production environments
Requirements
- Strong experience working with large, complex, real‑world datasets, ideally in aviation or related industries
- Expertise in data wrangling, feature engineering, and building scalable data pipelines
- Deep expertise in at least one advanced analytics area, with experience across several of the following: predictive modelling on tabular data, deep learning, NLP and large language models, generative AI pipelines, simulations, graph‑based models, time‑series forecasting, geospatial modelling, causal inference, reinforcement learning, optimisation, or anomaly detection
- Proven experience deploying, or partnering to deploy, customer‑facing machine learning systems into production
- Ability to collaborate across disciplines and communicate technical concepts to non‑technical audiences
Benefits
We are delighted to offer country specific benefits. Please visit the dedicated benefits page for details.
EEO Statement
We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law.
Principal Data Scientist I employer: RELX INC
As a Principal Data Scientist at our company, you will thrive in a dynamic work culture that values innovation and collaboration, particularly within the aviation analytics sector. We offer exceptional employee growth opportunities through mentorship and hands-on experience with cutting-edge technologies, all while enjoying a supportive environment that champions diversity and inclusion. Join us to make a meaningful impact while advancing your career in a location that fosters both professional and personal development.
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We think you need these skills to ace Principal Data Scientist I
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Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
