At a Glance
- Tasks: Lead the strategy and development of AI and machine learning products at Virgin Atlantic.
- Company: Join Virgin Atlantic, a leading airline with a focus on innovation and technology.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborate with diverse teams in a dynamic environment focused on cutting-edge technology.
- Why this job: Make a real impact by shaping data science products that drive business value.
- Qualifications: Experience in data science, machine learning, and product management is essential.
The predicted salary is between 63000 - 77000 £ per year.
Virgin Atlantic is looking for a
Manager - Data Product (Data Science) to lead the strategy, development and adoption of machine learning and AI products across the business.
This is a specialist product role for someone who understands data science in practice.
You will need to have hands‑on experience working with data science teams, machine learning models, statistical testing and AI solutions, with the credibility to challenge technical choices, shape model‑led products and translate complex methods into business value.
You will own the roadmap for data science products, working closely with data scientists, data engineers, technology teams, delivery partners and senior stakeholders.
The role will focus on identifying high‑value opportunities, defining product requirements, supporting model development and deployment, and ensuring that data science products are scalable, well‑governed and adopted by users.
We are looking for someone who can operate at the intersection of data science, technology and product management.
You should be comfortable discussing model performance, experimentation, data quality, deployment considerations and user needs, while also managing priorities, stakeholder expectations and measurable business outcomes.
- Day to Day
- Develop and manage the roadmap for machine learning, AI and data science products.
- Work with data scientists and engineers to shape, build, test and deploy models and AI‑enabled solutions.
- Translate business problems into clear product requirements for data science delivery teams.
- Use your technical understanding to support decisions around model design, experimentation, scalability and performance.
- Engage senior stakeholders to communicate product value, progress, risks and outcomes.
- Drive adoption of data science products through strong user engagement, communication and support.
- Maintain product quality standards across data integrity, governance, usability and business impact.
- Stay close to emerging data science, ML and AI techniques and identify opportunities to apply them effectively.
About You
- Strong experience in data science, machine learning, AI or a closely related technical field.
- Hands‑on experience building, developing, testing or deploying data science models or AI solutions.
- Good working knowledge of ML techniques, statistical testing, model performance and experimentation.
- Experience with tools such as Python, R, SQL, Tensor Flow, Py Torch, Azure, AWS or similar technologies.
- Product management experience, including roadmap ownership, prioritisation, requirements gathering and stakeholder engagement.
- Ability to work with both technical teams and non‑technical business stakeholders.
- Strong communication skills, with the ability to explain complex models, algorithms and insights clearly.
- Experience delivering data science products that have created measurable business value.
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Data Product Manager (Data Science) in Crawley employer: Virgin Atlantic
Virgin Atlantic is an exceptional employer, offering a dynamic work environment where innovation and teamwork thrive. With a commitment to employee growth, the company provides extensive training opportunities and a supportive culture that values safety and excellence in aircraft maintenance. Located in London, employees enjoy a vibrant city life alongside a competitive benefits package, making it a rewarding place to build a career in aviation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Product Manager (Data Science) in Crawley
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Virgin Atlantic!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Product Manager (Data Science) at Virgin Atlantic.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Virgin Atlantic.
✨Apply Directly through Our Website
When you find a suitable opening like Data Product Manager (Data Science) at Virgin Atlantic, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Product Manager (Data Science) in Crawley
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Virgin Atlantic, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Virgin Atlantic. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Virgin Atlantic
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Virgin Atlantic!
✨Prepare for Case Studies
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.
