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Senior Product Analyst - Recommend

75,000-100,000 GBP
  1. Analytics
  2. London

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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 life 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.


Job Description

We are looking for a Senior Product Analyst to support the biggest driver of new users at Wise, the Recommend channel (think refer-a-friend). You should be passionate about our mission of Money Without Borders as this role can have a critical impact on the mission. You will work with a product team to build scalable recommendation programs and partner up with marketing teams to drive strategy and growth by providing data driven insights and recommendations.

In this role, you will have a unique opportunity to work with a rich dataset and uncover insights as well as build tools to help people around the world be aware of Wise.

Your mission:

At Wise our mission is ‘Building the best way to move and manage the world's money

Min fees. Max ease. Full speed.' Whether our customers are sending money to another country, spending money abroad, or making and receiving international business payments, Wise is on a mission to make their lives easier and save them money.

Here’s how you’ll be contributing:

  • Owning the Recommend data and analytical domains and proactively making recommendations based on insights with experience in recommendations or referrals advantageous

  • Contribute to, own, create and track OKRs for your team, keeping them accountable throughout the quarter

  • Own measurement & attribution in Invite: you collaborate with your team on how to track and quantify the growth your channel drives and how it is measured and controlled for incremental effects

  • Optimise performance per country/program by running A/B tests and deep analysis into segments (RFM), lifetime values (LTVs), return on investment etc.

  • Opportunity exploration, sizing and then reporting on actual performance to senior stakeholders

  • Improve how your channel forecasts performance and inputs recommendations to the investment framework

  • Own optimisation data products in Recommend by working closely with your team, you identify what data and modelling needs to be collected & automated to build data products that enable maximal sustainable growth. This includes managing data pipelines


Qualifications

  • You have a background working in either product analytics and have ideally worked on invite or referral programs before

  • You have advanced SQL skills; Python/R skills are advantageous; familiar with data pipelines (we use dbt)

  • You’ve successfully set up and run A/B tests before and have a strong understanding of testing and experimental design

  • Able to demonstrate that you can tell a story and proactively give guidance on strategy based on insights

  • You are familiar with common marketing concepts (how different channels work, Payback, CAC, LTV, Contribution Margin, etc.)

  • You have experience with data visualisation tools (Looker, PowerBI, Tableau etc.) and demonstrate storytelling ability with data


Additional Information

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.

  1. London
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