Additionalinformation

Additional Information

Nice to have but not essential:

• Hands-on experience with any of Snowflake, dbt, Git, Airflow or Lightdash.
• Exposure to A/B testing or causal inference, in a course or in practice.
• An internship or project in analytics, data science, product or finance.
• An interest in payments, fintech, or how people move and manage money across borders.

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.

Keep up to date with life at Wise by following us on LinkedIn and Instagram.

Companydescription

Company Description

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.

More about our mission and what we offer.

Jobdescription

Job Description

As a Graduate Product Analyst, you’ll join our North America Regional Analytics team in September 2027. This full-time role is a chance to make a real impact early and kickstart your career. You’ll be onboarded with the global Graduate cohort in one of our offices and learn the basics of being a Wiser. The Role: We’re hiring three graduates to work as analysts inside our North America product teams, which build Wise for personal and business customers in the US and Canada. Our analysts don’t sit in a central reporting team: each one works day to day with product managers & engineers and helps them decide what to build next and whether it worked. You’ll join one of four teams: Onboarding, Send, Account or Growth. Each owns a different stage of the customer’s journey with Wise, and each is described below. You won’t be on your own. A senior analyst will mentor you, review your work and help you grow, and you’ll be part of a team of analysts covering the whole North America product. What you’ll be doing:

• Shape Strategy & Prioritization: You’ll help your team understand where customers struggle and what is worth fixing first. That means digging into funnels and customer behavior, reading customer feedback and survey responses, and sizing opportunities so the team can prioritize the work with the biggest impact. As you grow, you’ll lead your own discoveries and present recommendations to your product manager.
• Learn Launch Rigor & Experimentation: You’ll help design and analyze A/B tests and pre/post comparisons for new features, and learn to turn the results into a clear call: roll out, iterate or roll back. You’ll keep an eye on your team’s core metrics and flag when something looks wrong.
• Build on the Semantic Layer: We believe analysts add the most value when they focus on product discovery, not ad-hoc requests. You’ll learn to build and maintain the data models and dashboards that let your team answer their own questions, using Snowflake, dbt, Git, Airflow, Python and Lightdash, and help improve the AI skills that run our routine reporting.
• Share What You Learn: You’ll explain your findings to your team and the wider NorthAm squad, in writing, in charts and in person, so that your work leads to a decision.

How we work with AI: We lean hard into AI: AI skills produce our routine work and deep dives, so our analysts can focus on discovery. You’ll use AI tools every day, and you’ll own the answer, not the tool: checking the data, the logic and the conclusion before anyone acts on it. Where you could join:Onboarding Onboarding owns the first steps of a customer’s journey: creating a profile, getting verified (Know Your Customer / Know Your Business checks) and taking a first action with Wise. It also keeps financial crime out at the front door. The core challenge is letting genuine customers through quickly while stopping bad actors. You might work on questions like:

• Where do new customers drop out between signing up and their first transfer, and what would bring them back?
• Which verification steps slow genuine customers down without catching more fraud or financial crime?

Send Send covers what happens when a customer sends money, and is made up of three teams:

• Pay-in: how customers pay money into Wise, for example by bank transfer (ACH) or card. Which payment methods help customers complete their transfer, and what does each one cost us?
• Payout: how money reaches recipients’ bank accounts in the US and Canada, balancing three levers: cost, speed and conversion. What would make these payouts faster or cheaper, and how much more volume would that bring? You’ll also help track the health of our banking partners.
• Payment Risk: transfer suspensions and ACH and card chargebacks. How do we cut losses from chargebacks and fraud without blocking good customers?

Account Account owns how customers use Wise as an account, not only for one-off transfers: getting paid into Wise with USD and CAD local account details, spending with the Wise debit card, and earning a return on money held with Wise. You might work on questions like:

• What makes a customer start getting paid into their Wise account, and what makes them keep doing it?
• Who uses the Wise card, for what, and what stops others from using it?
• Does holding money with Wise change how customers send money abroad?

Growth Growth owns the top of the funnel: how people find Wise and decide to try it. That covers landing pages, the promotion engine, corridor strategy (which country-to-country routes we focus on) and pricing, where you’ll work with our Pricing Data Science team to understand how price affects demand. You might work on questions like:

• Did a promotion bring in customers who stay, or customers who leave once it ends?
• Which corridors should we focus on next, and why?

Your first six months:

• By three months: you own part of your team’s regular metrics and have delivered your first analysis.
• By six months: you’ve led a discovery or an experiment readout from question to recommendation and presented it to your team.

Qualifications

Qualifications What you’ll bring:

• Education: A bachelor’s or master’s degree in a quantitative field such as economics, statistics, mathematics, computer science or engineering, completed by your start date, or equivalent practical experience.
• Technical Foundations: You’ve used SQL, Python or R to answer a real question with data, in a course, a project, an internship or on your own. You understand the basics of statistics, such as distributions, hypothesis tests and confidence intervals, and can tell when a difference is real rather than noise.
• Curiosity & Product Sense: You want to know why customers behave the way they do, and you ask “so what should we do?” about every result.
• Clear Communication: You can explain a finding to someone who isn’t technical, in writing and in conversation, and you’re comfortable saying “I don’t know yet”.
• Ownership: You finish what you start, ask for help early and act on feedback.
• AI with Judgment: You use AI tools to work faster, and you check their output before you trust it.
• Right to Work: You must be authorized to work in the US. We’re unable to offer visa sponsorship for this role.