Head of Data Science (Data and Analytics)

easyJet
London
2 months ago
Applications closed

Related Jobs

View all jobs

Head of Data Science and Analytics

Head of Data Science

Head of Data Science and Analytics

Head of Data Science and Analytics

Head of Data Science & Analytics

Head of Data Science and Analytics

Description

The role: Head of Data Science (Data & Analytics)

We kindly encourage you to submit your application by Monday, 17th February, as this will be the closing date for submissions.

About The Role:We are seeking a Head of Data Science to lead easyJets Data Science Centre of Enablement. This pivotal role will shape and drive our data science strategy, ensuring alignment with business objectives and enhancing our capabilities in machine learning and advanced analytics. The successful candidate will drive initiatives to transform complex business challenges into innovative data-driven solutions, enhancing customer experience and driving sustainable growth.

What Youll be Doing:

  1. Strategic Leadership:Develop and implement a comprehensive data science strategy that integrates seamlessly with company objectives. Collaborate with key stakeholders across business domains to identify opportunities for leveraging data to drive growth and efficiency.
  2. Data Science and Machine Learning Enablement:Lead the Centre of Enablement for Data Science, guiding the development and application of sophisticated analytical models (ML) and tools. Ensure best practices in advanced analytics are maintained and evolved.
  3. Collaboration and Influence:Work closely with cross-functional teams to prioritise and drive data science projects. Build strong partnerships within the data community and ensure alignment with business needs.
  4. Technology and Innovation:Stay at the forefront of emerging technologies in AI and machine learning (ML). Mentor and develop the data science team, fostering a culture of innovation and continuous improvement.
  5. Governance and Compliance:Ensure all data science activities adhere to industry regulations and company policies. Maintain a robust data governance framework to ensure the ethical use of data.

Requirements of the Role

What Youll Bring to the Team:

  1. Proven experience in leading data science initiatives, with a strong background in data science, machine learning, AI, and advanced analytics.
  2. Expertise in programming languages such as Python, R, and SQL, and tools like Tableau and ThoughtSpot.
  3. Strong leadership skills, capable of mentoring and developing a high-performing team.
  4. Excellent communication skills, with the ability to articulate complex technical details to non-technical stakeholders.
  5. A strategic thinker with outstanding problem-solving capabilities and a track record of delivering impactful data-driven solutions.

What We Offer in Return:

  1. Competitive base salary with a 30% bonus potential.
  2. Private medical cover.
  3. 25 days holiday, plus bank holidays.
  4. Attractive pension scheme (7% company contribution).
  5. Life Assurance and a flexible benefits package.
  6. Exceptional staff travel benefits.
  7. Opportunities for professional development in a supportive and dynamic environment.

Location & Hours of Work:This full-time role is based in Luton 60% of the month, with a 40-hour work week.

Join easyJet to lead the way in data science innovation and help us harness the power of data to revolutionise the travel experience. Apply today to become part of our ambitious journey.

J-18808-Ljbffr

Get the latest insights and jobs direct. Sign up for our newsletter.

By subscribing you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Jobs

Portfolio Projects That Get You Hired for Machine Learning Jobs (With Real GitHub Examples)

In today’s data-driven landscape, the field of machine learning (ML) is one of the most sought-after career paths. From startups to multinational enterprises, organisations are on the lookout for professionals who can develop and deploy ML models that drive impactful decisions. Whether you’re an aspiring data scientist, a seasoned researcher, or a machine learning engineer, one element can truly make your CV shine: a compelling portfolio. While your CV and cover letter detail your educational background and professional experiences, a portfolio reveals your practical know-how. The code you share, the projects you build, and your problem-solving process all help prospective employers ascertain if you’re the right fit for their team. But what kinds of portfolio projects stand out, and how can you showcase them effectively? This article provides the answers. We’ll look at: Why a machine learning portfolio is critical for impressing recruiters. How to select appropriate ML projects for your target roles. Inspirational GitHub examples that exemplify strong project structure and presentation. Tangible project ideas you can start immediately, from predictive modelling to computer vision. Best practices for showcasing your work on GitHub, personal websites, and beyond. Finally, we’ll share how you can leverage these projects to unlock opportunities—plus a handy link to upload your CV on Machine Learning Jobs when you’re ready to apply. Get ready to build a portfolio that underscores your skill set and positions you for the ML role you’ve been dreaming of!

Jobs Careers

Machine Learning Job Interview Warm‑Up: 30 Real Coding & System‑Design Questions

Machine learning is fuelling innovation across every industry, from healthcare to retail to financial services. As organisations look to harness large datasets and predictive algorithms to gain competitive advantages, the demand for skilled ML professionals continues to soar. Whether you’re aiming for a machine learning engineer role or a research scientist position, strong interview performance can open doors to dynamic projects and fulfilling careers. However, machine learning interviews differ from standard software engineering ones. Beyond coding proficiency, you’ll be tested on algorithms, mathematics, data manipulation, and applied problem-solving skills. Employers also expect you to discuss how to deploy models in production and maintain them effectively—touching on MLOps or advanced system design for scaling model inferences. In this guide, we’ve compiled 30 real coding & system‑design questions you might face in a machine learning job interview. From linear regression to distributed training strategies, these questions aim to test your depth of knowledge and practical know‑how. And if you’re ready to find your next ML opportunity in the UK, head to www.machinelearningjobs.co.uk—a prime location for the latest machine learning vacancies. Let’s dive in and gear up for success in your forthcoming interviews.

Jobs

Negotiating Your Machine Learning Job Offer: Equity, Bonuses & Perks Explained

How to Secure a Compensation Package That Matches Your Technical Mastery and Strategic Influence in the UK’s ML Landscape Machine learning (ML) has rapidly shifted from an emerging discipline to a mission-critical function in modern enterprises. From optimising e-commerce recommendations to powering autonomous vehicles and driving innovation in healthcare, ML experts hold the keys to transformative outcomes. As a mid‑senior professional in this field, you’re not only crafting sophisticated algorithms; you’re often guiding strategic decisions about data pipelines, model deployment, and product direction. With such a powerful impact on business results, companies across the UK are going beyond standard salary structures to attract top ML talent. Negotiating a compensation package that truly reflects your value means looking beyond the numbers on your monthly payslip. In addition to a competitive base salary, you could be securing equity, performance-based bonuses, and perks that support your ongoing research, development, and growth. However, many mid‑senior ML professionals leave these additional benefits on the table—either because they’re unsure how to negotiate them or they simply underestimate their long-term worth. This guide explores every critical aspect of negotiating a machine learning job offer. Whether you’re joining an AI-focused start-up or a major tech player expanding its ML capabilities, understanding equity structures, bonus schemes, and strategic perks will help you lock in a package that matches your technical expertise and strategic influence. Let’s dive in.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.