At a Glance
- Tasks: Lead a team of analysts to drive data solutions and insights for a growing FinTech.
- Company: Join a dynamic Payments FinTech backed by a major UK bank.
- Benefits: Competitive salary, career growth, and the chance to work with cutting-edge technology.
- Other info: Collaborative environment with opportunities to innovate and grow.
- Why this job: Make a real impact on business strategy through data-driven decisions.
- Qualifications: Strong experience in data analysis, SQL, and leadership skills required.
The predicted salary is between 31500 - 38500 £ per year.
About the role
A fantastic opportunity to join as Data Analytics Lead for a growing Payments FinTech backed by one of the largest banks in the UK.
As Data Analytics Lead you will drive value for the customer through sourcing and data transformation. You’ll be working closely with core technology and architecture teams to deliver strategic data solutions, while driving Agile and DevOps adoption in the delivery of data engineering.
Key requirements:
- Managing and growing a team of analysts
- Strong experience in data analysis and reporting with extensive experience of SQL, PowerBI or similar tooling, ETL pipelines
- Leading the analytics strategy, while still being hands on in terms of analysis
- Ensuring that relevant insight and analysis is provided to drive growth
- Experience of Synapse, Azure Data Lake, Azure Data Factory, highly desirable
- Working closely with other senior stakeholders on the overall business strategy
- Proficient understanding of cloud data solutions and principles
Lead Data Analyst in Whitehall employer: RedCat Digital
Join a leading global media and publishing organisation that values its employees and fosters a collaborative work culture. With a focus on professional growth, you will have the opportunity to work closely with senior stakeholders while providing impactful legal advice across international employment law matters. Enjoy a flexible working pattern of 4 days in the office and 1 day remote, alongside competitive compensation and the chance to contribute to meaningful projects in a dynamic environment.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Analyst in Whitehall
✨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 RedCat Digital!
✨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 Lead Data Analyst at RedCat Digital.
✨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 RedCat Digital.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Analyst at RedCat Digital, 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 Lead Data Analyst in Whitehall
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 RedCat Digital, 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 RedCat Digital. 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 RedCat Digital
✨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 RedCat Digital!
✨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.
