Salary: Competitive
Hours: Full Time
Location: Hybrid working -The VHQ Crawley 3x days on site and 2x days from wfh
Contract: Permanent
Closing Date: 1st December 2024
Are you passionate about AI and machine learning? As the Manager - Data Product (Data Science) at Virgin Atlantic, you'll lead the transformation of data into actionable insights, empowering decision support for colleagues and customers through AI-driven products.
In this role, you'll guide the development of high-performance, scalable AI solutions, collaborating closely with data scientists, engineers, and top development partners. You’ll engage stakeholders to ensure our products deliver measurable value, and stay ahead of the latest ML and AI advancements to drive continuous improvement.
Your focus on quality, standards, and user adoption will make a lasting impact, helping Virgin Atlantic leverage AI innovation at scale.
If you’re ready to lead in AI and make a real difference, this is your opportunity to elevate your career with Virgin Atlantic.
- Drive the development and execution of data science & compound AI products, collaborating closely with diverse teams.
- Determine data requirements and develop strategies for data collection, storage, and analysis.
- Successfully implement machine learning algorithms and predictive models to extract valuable insights from data – managed as products that may include custom simulation applications, consumable endpoints and natural language interfaces (via LLMs and other frontier model components).
- Promote the implementation of effective approaches and uphold superior quality standards in data management and analysis – ensuring the veracity and explainability of model outputs and recommended or automated action.
- Work closely with key individuals to gain insights into business requirements and transform them into practical solutions.
- Provide guidance and mentorship to the data product and data science teams, fostering a culture of learning and growth.
- Demonstrated proficiency in data science, machine learning or data engineering with a focus on developing and implementing data products.
- Advanced degree (Master's or PhD) in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, or a related discipline, or equivalent practical experience.
- Strong knowledge of statistical analysis, machine learning, and data visualisation techniques.
- Exhibited curiosity and experimentation with LLMs and other frontier models and a strong understanding of how to navigate the current landscape of proprietary and open-source models and paradigms.
- Strong proficiency in data science tools and technologies such as Python, R, TensorFlow, PyTorch, SQL, and cloud-based platforms like Azure or AWS.
- Demonstrated drive and motivation, consistently delivering impactful data solutions.
- Effective communication skills and the ability to influence.
At Virgin Atlantic, our leaders empower teams to thrive through collaboration, innovation, and excellence. Explore our Leadership Recipe and discover the 20 core ingredients that define what it means to lead with us, driving our mission to be the most loved travel company and achieve sustainable profit. Want to learn more? Click here
Our customers come from all walks of life and so do our colleagues. That’s why we’re proud to be an equal opportunity employer and actively encourage applications from all backgrounds. At Virgin Atlantic, we believe everyone can take on the world - no matter your age, gender, gender identity, gender expression, ethnicity, sexual orientation, disabilities, religion, or beliefs. We celebrate difference and everything that makes our colleagues unique by upholding an inclusive environment in which we can all thrive. So that everyone at Virgin Atlantic can be themselves and know they belong.
To make your journey with us accessible and individual to you, we encourage you to let us know if you’d like a little extra help with your application, or if you have any individual requirements at any stage along your recruitment journey. We are here to support you, so please reach out to our team, ([email protected]) feeling confident that we’ve got your individual considerations covered.