At a Glance
- Tasks: Deliver impactful data solutions and support product performance with actionable insights.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Competitive salary, flexible work, private medical insurance, and annual self-development budget.
- Other info: Enjoy a dynamic environment with opportunities for growth and a pet-friendly office.
- Why this job: Make a real difference in the world of payments while working remotely.
- Qualifications: Experience in payments, proficiency in SQL, and strong analytical skills.
The predicted salary is between 60000 - 85000 £ per year.
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. For everyone, everywhere.
Responsibilities:
- You will deliver high-impact, scalable data solutions such as building and maintaining robust models and data products that directly support the team's efficiency, effectiveness and risk appetite.
- You will proactively manage team KPIs, ensuring clear measurement and understanding of product performance, undertaking deep-dives and providing actionable recommendations to drive product objectives and roadmap.
- You will be leveraging advanced analytics, crafting dashboards and visualisations that bring product performance data to life, tell a clear story, and offer diagnostic power.
- You will conduct opportunity sizing for product initiatives to understand short-term and long-term impacts against key performance indicators and our long term vision.
- You will support product discovery through initiatives such as market sizing, research, and scenario modelling to inform the product roadmap.
Requirements:
- You have experience working in payments and/or banking.
- You are proficient with SQL and know your way around data pipeline management tools such as Snowflake, dbt, Git, Airflow, Python, and Lightdash.
- You're comfortable owning analytics from data transformation through to delivering actionable insights.
- You are commercially minded, able to translate your analysis into impact and comfortable with opportunity sizing, prioritisation and scenario modelling.
- You have experience working in a high-growth B2B tech environment and have worked closely with product teams before.
- You are solution-oriented and able to own projects from start to finish.
- You are comfortable motivating stakeholders across Wise and negotiating timelines to unblock yourself and make things happen!
- You are an excellent communicator, able to form your own opinions and effectively articulate them to influence key stakeholders.
- You should also be comfortable writing and maintaining clear and concise documentation and analysis.
Desirable:
- A plus if you’re familiar with FX products, and correspondent banking.
- Proficient in python’s various data transformation, visualisation and statistics libraries i.e. pandas, numpy, scipy and plotly.
- Experience leading a team or owning a whole product domain.
Conditions:
- Base salary of £60k - £85k (based on experience).
- RSUs in a growing and publicly listed company.
- Work from (almost) anywhere in the world for up to 90 days a year.
- Flexible working - you’re trusted to do the right thing and be responsible.
- Private Medical Insurance + Life Insurance.
- Discounted gym memberships and cycle to work scheme.
- A paid 6-week sabbatical leave after four years.
- 26 weeks maternity leave at full pay.
- An annual self-development budget.
- Annual Mission Days festival.
- Pet friendly offices.
Product analyst in payments in London employer: Wise
Wise is an exceptional employer that fosters a culture of inclusivity and innovation, making it an ideal place for a Lead ML / Data Scientist to thrive. With a hybrid working model, generous personal development budgets, and a commitment to employee growth, you will have the flexibility and resources to excel in your role while contributing to meaningful projects that redefine how money moves globally.
StudySmarter Expert Advice🤫
We think this is how you could land Product analyst in payments in London
✨Get Involved in Data Science Meetups
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We think you need these skills to ace Product analyst in payments 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.
