At a Glance
- Tasks: Lead data analysis to drive financial insights and improve pricing strategies.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, inclusive culture, and opportunities for career progression.
- Other info: Be part of an inclusive team that values respect and empowerment.
- Why this job: Make a real impact in Fintech while working with advanced analytics tools.
- Qualifications: 5+ years in data analytics, strong SQL skills, and experience in Fintech.
The predicted salary is between 70000 - 90000 £ per year.
Wise is a global technology company, building the best way to move and manage the world’s money. As part of our team, you will be helping us create an entirely new network for the world's money. We are looking for a Lead Data Analyst to join the Wise Platform Pricing Analytics team at Wise. The Wise Platform Pricing Analytics team manages the pricing model and P&L analysis for Wise Platform. The team supports Wise Platform by calculating prices for partners, monitoring and reviewing the financial sustainability of the program, and finding opportunities to continue improving the growth and profitability of the company.
Responsibilities include:
- Lead deep-dive investigations into complex cost data, driving improvements in upstream data quality and revenue and cost allocation methodologies within the Product Economics domain.
- Monitor and review the financial performance of Wise Platform, surfacing insightful and actionable insights on the main drivers of profitability.
Requirements:
- 5+ years of experience in data analytics.
- Advanced stakeholder management skills.
- Extensive experience using SQL to build and maintain complex data sources, and leveraging visualisation tools to surface critical insights.
- Experience with dbt and robust data modelling, including the ability to navigate complex dbt projects and create reusable, maintainable data assets for scalable analytics.
- Experience working in Fintech or Financial Services.
- Knowledge of advanced analytics techniques, including the use of Python and statistical modelling.
We're people building money without borders — without judgement or prejudice, too. Inclusive teams help us live our values and make sure every Wiser feels respected, empowered to contribute towards our mission and able to progress in their careers.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Analyst Python SQL in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Lead Data Analyst Python SQL in London
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 Wise, 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 Wise. 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 Wise
✨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 Wise!
✨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.
