Data Scientist - Customer Understanding

Wise; London; On-site; GBP 45,000 - 70,000; Full time

Job summary

A leading technology company is seeking a Data Scientist for its Marketing Team in London. The role focuses on developing predictive models to enhance marketing effectiveness and support growth strategies. Applicants should have a strong background in statistical methods and experience with tools like PyTorch and Python. Join a diverse team committed to making money transfer easier for everyone.

Benefits

Impact on marketing strategies

Autonomy in project development

Diversity within the team

Qualifications

• Experience with LTV modeling and econometrics.
• Strong statistical background with Bayesian reasoning skills.
• Ability to own projects end-to-end with effective time management.

Responsibilities

• Identify growth opportunities and develop predictive models.
• Model customer behavior data and optimize campaign delivery.
• Collaborate with data analysts to enhance model understanding.

Skills

Predictive modeling

Customer Lifetime Value (LTV)

Causal inference

Bayesian methods

Python

Statistical analysis

Tools

PyTorch

Kafka

Docker

Job description

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Data Scientist - Customer Understanding, London

Client: Wise

Location: London, United Kingdom

Job Category: Other

EU work permit required: Yes

Job Reference: 14c4526d3d5d

Job Views: 19

Posted: 22.06.2025

Expiry Date: 06.08.2025

Job Description:

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.

Job Description

Data Scientist - Marketing

We’re looking for a Data Scientist to join our growing Marketing Team in London. This role offers a unique opportunity to impact, grow as a Data Scientist, and help save people money.

Your mission:

Wise has pioneered new ways for people to transfer money across borders and currencies. Our customers can also manage their hard-earned money with the world’s first platform to offer true multi-currency account. Your mission is to help make people aware of Wise as a solution for cross-border money needs.

Here’s how you’ll contribute to Marketing:

• Help the Marketing team identify the biggest opportunities for growth.
• Develop predictive models to calculate Customer Lifetime Value (LTV), aiding in prioritizing marketing efforts and resource allocation.
• Model customer behavior data and product usage to identify target audiences and effective strategies.
• Use causal models to measure the impact of CRM and Invite campaigns on business metrics, applying causal inference to optimize campaign delivery.
• Assist in understanding which growth activities to invest in via Marketing Mix Models.
• Collaborate with Data Analysts to help them understand and utilize models you develop (LTV or MMM models).
• Build, maintain, evaluate, and communicate insights from models to support marketing strategies.

This role offers:

• Impact: Partner with marketing teams to help millions learn about Wise.
• Autonomy: Work independently to create your own vision with team support.
• Diversity: Be part of a team of Data Scientists, Analysts, and Marketers.
• Mission: Contribute to making money without borders the new normal.

Qualifications:

• Experience with LTV modeling, econometrics, and marketing mix modeling.
• Knowledge of Bayesian methods, neural networks (preferably PyTorch).
• Strong statistical background, especially Bayesian reasoning.
• Experience with causal inference models.
• Proficiency in various modeling techniques: gradient boosting, neural networks, linear regression.
• Expertise in Python, capable of developing REST services or UI components.
• Understanding of Kafka, Docker, and related technologies.
• Ability to own projects end-to-end.
• Data-driven, structured, and effective time management.
• Ability to see the bigger picture and communicate insights clearly.

Additional Information:

At Wise, we value diversity, equity, and inclusion. We celebrate our international team and strive for an inclusive environment where everyone can contribute and grow. To learn more about working at Wise, follow us on our social platforms.