At a Glance
- Tasks: Analyse data to drive insights and support our AI transformation in holiday booking.
- Company: Join Awaze, Europe's largest managed vacation rentals and holiday resorts business.
- Benefits: Enjoy competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and real impact.
- Why this job: Be part of an exciting AI journey that reshapes holiday planning for millions.
- Qualifications: Strong analytical skills and a passion for data-driven decision making.
The predicted salary is between 63000 - 77000 £ per year.
The way people discover and book holidays is changing, and we're rebuilding our technology for what comes next.
We are Awaze, Europe’s largest managed vacation rentals and holiday resorts business, bringing together some of the continent’s most recognised travel brands, including cottages. com, Hoseasons, NOVASOL and James Villa Holidays.
With more than 1.5 million bookings every year, 100,000+ properties and customers across Europe, we already operate at serious scale.
But the next chapter for Awaze is about much more than scale.
We’re embarking on an ambitious AI transformation that will reshape how our customers discover, plan and book their holidays, and how our engineering teams build the technology behind those experiences.
Our strategy spans AI-powered search, natural-language discovery, intelligent recommendations, richer property data and AI-assisted engineering, all underpinned by a platform built around speed, trust, quality and real-time data.
Position: Data Insights Analyst Reports to: Chief Data Officer The Role Working with our Chief Data Officer, you will act as an internal data
Data Insight Analyst employer: Awaze
Awaze is an exceptional employer that fosters a dynamic and innovative work culture, perfect for those looking to make a significant impact in the travel industry. With a strong focus on employee growth and development, you will have access to unique opportunities to lead cross-functional teams and shape the future of ancillary revenue. Located in a vibrant environment, Awaze offers competitive benefits and a collaborative atmosphere that values creativity and strategic thinking.
StudySmarter Expert Advice🤫
We think this is how you could land Data Insight Analyst
✨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 Awaze!
✨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 Insight Analyst at Awaze.
✨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 Awaze.
✨Apply Directly through Our Website
When you find a suitable opening like Data Insight Analyst at Awaze, 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 Insight Analyst
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 Awaze, 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 Awaze. 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 Awaze
✨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 Awaze!
✨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.
