At a Glance
- Tasks: Lead a data science team to enhance customer holiday experiences using AI and machine learning.
- Company: Join loveholidays, a leading Online Travel Agency dedicated to making holidays accessible for everyone.
- Benefits: Enjoy 25 days of holiday, discounted trips, training budgets, and a 5% pension contribution.
- Why this job: Be part of a mission-driven team that values innovation, personal growth, and diverse perspectives.
- Qualifications: Proven experience in data science, mentoring, and strong knowledge of machine learning and programming languages.
- Other info: Collaborate with senior leadership and shape the future of travel technology.
The predicted salary is between 43200 - 72000 £ per year.
At loveholidays, we’re on a mission to open the world to everyone, giving our customers unlimited choice, unmatched ease, and unmissable value for their next getaway. Our team is the driving force behind our role as our customers’ personal holiday expert — the smart way to get away.
About the team
Our data science team (currently four data scientists, and we’re hiring two more) works across the business to deploy machine learning approaches that help us realize our ambition of becoming Europe’s most loved Online Travel Agency. The team focuses on building value for our customers, suppliers, and loveholidays through deploying advanced machine learning techniques.
The impact you’ll have
Reporting to the Chief Data Officer, the Head of Data Science will help the business deliver AI-powered solutions to assist customers pre- and post-booking:
- Drive conversion rate improvements by helping customers find their ideal holiday through sort order and recommendation algorithms.
- Drive more efficient traffic acquisition through bid optimization algorithms.
- Help the business make better data-assisted decisions through A/B test analysis reporting.
- Work across the business to ensure we are choosing the right applications for machine learning technology.
- The Head of Data Science is also responsible for creating and developing our data science talent through hiring, line management, and career progression.
Key responsibilities include:
- Building a deep understanding of the business to develop a company-wide data science strategy.
- Help the business, including your team, prioritize the highest impact data science initiatives.
- Collaborating closely with senior leadership and the wider business.
- Build a reputation for getting things done.
- Bring data leadership and rigor to improve decision-making.
- Manage stakeholder relationships across functions like engineering, product, operations, and the Executive Team.
- Structuring complex data science projects to deliver incremental commercial value.
- Building and running complex machine learning systems within the data science team and with engineering teams.
- Ensure adoption of engineering principles in data science applications.
- Developing and scaling a high-performing team of data scientists through hiring, coaching, and career development.
Qualifications include a proven track record in unlocking commercial value through data science, mentoring skills, and strong knowledge of machine learning and statistical algorithms focused on structured data. Experience with cloud-based data science applications, performance, scalability, and reliability, along with expertise in Python and familiarity with other programming languages like TypeScript, Java, Golang, Rust, is required.
Perks of joining us
- Company pension contributions at 5%.
- Individualized training budget for on-the-job learning.
- Discounted holidays for you, your family, and friends.
- 25 days of holidays per year, increasing with service.
- Options to buy and sell annual leave.
- Cycle to work scheme, season ticket loan, and eye care vouchers.
At loveholidays, we focus on developing an inclusive culture that encourages personal growth and collective success. We value diverse perspectives and ideas that enhance our teams and the insight you could bring to our journey.
The interview journey
- Introductory chat with the hiring manager (Chief Data Officer).
- Cross-functional interviews covering your approach to leading the data science team and your technical expertise.
Note: Preparation prior to the interviews is required.
About the company
loveholidays offers a bespoke way of searching for your next getaway, allowing you to personalize your holiday with ultimate flexibility. Book confidently knowing your holiday is ATOL protected, with various payment options available.
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Head of Data Science employer: loveholidays
Contact Detail:
loveholidays Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Science
✨Tip Number 1
Familiarise yourself with loveholidays' mission and values. Understanding their focus on customer experience and data-driven decision-making will help you align your responses during interviews, showcasing how your vision for data science can contribute to their goals.
✨Tip Number 2
Prepare to discuss specific machine learning projects you've led that resulted in measurable business outcomes. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will demonstrate your ability to drive commercial value through data science.
✨Tip Number 3
Highlight your experience in building and managing high-performing teams. Be prepared to share examples of how you've mentored team members and fostered a collaborative environment, as this is crucial for the Head of Data Science role at loveholidays.
✨Tip Number 4
Research the latest trends in AI and machine learning, particularly in the travel industry. Being knowledgeable about current technologies and methodologies will not only impress the interviewers but also show your commitment to staying ahead in the field.
We think you need these skills to ace Head of Data Science
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and qualifications required for the Head of Data Science position. Tailor your application to highlight your relevant experience in machine learning, data science strategy, and team management.
Craft a Compelling CV: Your CV should clearly showcase your proven track record in unlocking commercial value through data science. Include specific examples of projects you've led, technologies you've used, and the impact of your work on previous employers.
Write a Strong Cover Letter: In your cover letter, express your passion for the travel industry and how your skills align with loveholidays' mission. Highlight your leadership experience and your approach to mentoring and developing a high-performing data science team.
Prepare for Interviews: Anticipate questions related to your technical expertise and leadership style. Be ready to discuss your experience with cloud-based data science applications and how you've driven conversion rate improvements or optimised traffic acquisition in past roles.
How to prepare for a job interview at loveholidays
✨Understand the Business
Before your interview, take the time to research loveholidays and understand their mission and values. Familiarise yourself with their data science initiatives and how they impact customer experience. This will help you demonstrate your alignment with their goals.
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with machine learning and statistical algorithms. Highlight specific projects where you've unlocked commercial value through data science. Make sure to mention your proficiency in Python and any other relevant programming languages.
✨Demonstrate Leadership Skills
As the Head of Data Science, you'll need to lead a team effectively. Be ready to share examples of how you've mentored others, managed teams, and prioritised high-impact initiatives. Discuss your approach to building a high-performing team and fostering a collaborative environment.
✨Prepare for Cross-Functional Collaboration
Since the role involves working closely with various departments, think about how you've successfully collaborated with stakeholders in the past. Prepare to discuss your strategies for managing relationships across functions like engineering, product, and operations.