At a Glance
- Tasks: Drive data-driven decisions to enhance payment systems and improve customer experiences.
- Company: Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, diverse team culture, and opportunities for professional growth.
- Other info: Collaborate with 150+ analysts in a dynamic, inclusive environment.
- Why this job: Join a mission to create Money Without Borders and make a real impact.
- Qualifications: Strong analytical skills and experience in payment operations.
The predicted salary is between 50000 - 70000 £ per year.
hackajob is collaborating with Wise to connect them with exceptional professionals for this role.
Wise is a global technology company, building the best way to move and manage the world's money. Min fees. Max ease. Full speed. Whether people and businesses are sending money to another country, spending abroad, or making and receiving international payments, Wise is on a mission to make their lives easier and save them money. As part of our team, you will be helping us create an entirely new network for the world's money.
THE ROLE
We are looking for a Senior Payment Operations Analyst who is passionate about our mission of Money Without Borders. You will partner with our Payment Operations organisation to help drive data-driven decisions that would improve the quality of our payment systems, making them smoother and more efficient. The Payment Operations organisation is responsible for ensuring that our customers' payments flow smoothly. The organisation focuses on resolving issues surrounding the movement of funds, to deliver a fast and convenient payment experience for our customers.
As a Senior Payment Operations Analyst, you will be driving our analytics effort to strengthen our quality assurance and control processes. You will identify how we can evaluate if payment processing flows are done right, and if not, what went wrong with them. You will own an attribution model to quality lapses, and work with other teams to improve the quality of payment processing. You will also be incorporating AI in your work, using AI to improve the quality review process.
This is a great opportunity for an analyst that has strong product thinking and is passionate about creating convincing analyses. It also allows you to work alongside the current developments in AI. You will also be part of a wider team of 150+ analysts that you can collaborate with on cross-team projects, have knowledge sharing sessions and bring ideas on how we can improve analytics across Wise. This is an IC2 role. Please note that Wise does not provide visa sponsorship for this role. Applicants must have the right to work in the UK.
WHAT YOU'LL BE DOING
- Collaborate with various senior stakeholders in the organisation and effectively communicate your insights into real change for our customers.
- Support the organisation's drive to improve the quality of its processes by identifying payment flows that have met quality standards, and if not, identify the reasons for failing quality standards.
- Proactively contribute to, own, create and track key metrics and results for the organisation, keeping them accountable throughout the quarter.
- Expose the vast amount of data available to the organisation in a meaningful and actionable way and support other teams in discovering insights from data.
- Support your team and the organisation by building and maintaining data pipelines, preparing reports, and creating visualisations.
For everyone, everywhere. We’re people building money without borders — without judgement or prejudice, too. We believe teams are strongest when they are diverse, equitable and inclusive. We’re proud to have a truly international team, and we celebrate our differences. 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.
If you want to find out more about what it's like to work at Wise visit Wise.Jobs.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Analyst - Payment Operations in Bristol
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Senior Data Analyst - Payment Operations in Bristol
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
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✨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.
