At a Glance
- Tasks: Design data foundations for real-time decisions and build core models for analytics and AI.
- Company: Leading logistics scale-up in Europe, transforming the industry with data-driven solutions.
- Benefits: Up to £100k salary, performance bonuses, enhanced parental leave, and VISA sponsorship available.
- Other info: Be part of a fast-paced environment with opportunities for growth and transformation.
- Why this job: Join a dynamic team at the forefront of innovation and make a real impact.
- Qualifications: 5+ years in analytics engineering, Python skills, and experience with data visualisation tools.
The predicted salary is between 63000 - 77000 £ per year.
Salary: up to £100k (strong mid/senior) up to 100% additional allotment based on performance
Enhanced parental leave
VISA sponsorship available if needed
This company is hands-down the hottest logistics scale up in Europe, taking the industry by storm and growing at an astronomical pace. Every parcel that moves through their network generates thousands of data points. Those data points feed forecasts, optimisation models, and an increasingly autonomous AI marketplace. The Analytics Engineer in this role owns the foundations that make all of it possible, sitting within the company's biggest and most data-rich squad. If you want to be at the heart of something genuinely transformative, this might be for you.
What you'll be doing:
- Designing the data foundations that power real-time operational decisions
- Building core data models that power analytics, data science and autonomous AI workflows
- Owning the data inputs that drive key AI decision systems
- Driving data quality through testing, monitoring and alerting
- Shaping analytics engineering practices as the business scales
Must have requirements:
- 5+ years in analytics engineering, data engineering or a similar role
- Experience with data visualisation tools
- Python proficiency for automation and data manipulation
- Clear communicator who can translate between technical and non-technical stakeholders
- Experience with orchestration tools (Dagster / Airflow)
- Familiarity with ML workflows and feature engineering
Analytics Engineer employer: Wave Group
Wave Group is an excellent employer, offering a dynamic work culture that fosters innovation and collaboration in the heart of London. Employees benefit from competitive salaries, flexible hybrid working arrangements, and opportunities for professional growth while contributing to impactful projects that modernize policing through advanced AI solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨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 Wave Group!
✨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 Analytics Engineer at Wave Group.
✨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 Wave Group.
✨Apply Directly through Our Website
When you find a suitable opening like Analytics Engineer at Wave Group, 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 Analytics Engineer
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 Wave Group, 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 Wave Group. 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 Wave Group
✨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 Wave Group!
✨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.
