At a Glance
- Tasks: Lead quality engineering for data and analytics platforms using AI-driven testing.
- Company: Join a prestigious European bank focused on innovation and quality.
- Benefits: Attractive salary, comprehensive benefits, and opportunities for professional growth.
- Other info: Collaborate with diverse teams and drive automation-first testing practices.
- Why this job: Make a significant impact in a dynamic environment with cutting-edge technology.
- Qualifications: Experience in quality engineering and strong leadership skills required.
The predicted salary is between 72000 - 88000 £ per year.
The European Bank for Reconstruction and Development is seeking a Senior Leader to head Quality Engineering across data, integration and analytics platforms. You will embed quality from design through operations, driving AI-powered testing and governance across Microsoft Fabric, EBX, Azure Integration Services, Informatica IDMC and Control-M.
You will lead automation-first testing in CI/CD, align QA practices with SOX, DORA and IFRS, and partner with engineers, data owners and business stakeholders.
AI-Driven QE Leader for Data & Analytics employer: European Bank for Reconstruction and Development
The European Bank for Reconstruction and Development is an exceptional employer, offering a dynamic work culture that prioritises employee well-being and professional growth. Located in the vibrant city of London, we provide comprehensive training opportunities and a supportive environment where your contributions to health and safety initiatives are valued. Join us to make a meaningful impact while enjoying the benefits of working in a diverse and inclusive organisation.
Contact Details:
European Bank for Reconstruction and Development Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land AI-Driven QE Leader for Data & Analytics
✨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 European Bank for Reconstruction and Development!
✨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 AI-Driven QE Leader for Data & Analytics at European Bank for Reconstruction and Development.
✨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 European Bank for Reconstruction and Development.
✨Apply Directly through Our Website
When you find a suitable opening like AI-Driven QE Leader for Data & Analytics at European Bank for Reconstruction and Development, 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 AI-Driven QE Leader for Data & Analytics
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 European Bank for Reconstruction and Development, 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 European Bank for Reconstruction and Development. 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 European Bank for Reconstruction and Development
✨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 European Bank for Reconstruction and Development!
✨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.