
Focused on global money transfers.
Senior Data Science Manager - Marketing at Wise
About the role
THE ROLE
We’re looking for a Senior Data Science Manager to lead the team building the models that power our global marketing engine. You’ll be the strategic partner to our Global Marketing teams, building the LTV, MMM, and CRM models that pinpoint exactly where Wise scales next.
This role is about bridging the gap between deep technical research and real-world impact. By ensuring our model outcomes are robust, transparent, and—most importantly—actionable, you’ll turn complex data science into the insights that drive our mission and reach millions of customers worldwide.
WHAT YOU’LL DO
- Drive Growth Strategy & Real Impact:
Partner with Analytics, Marketing Channels Leads, and Finance to define the strategy for our marketing investments across the globe. You will be responsible for quantifying and communicating the business value and ROI of our data science initiatives, translating complex insights into actionable strategies for senior leadership.
- Technical Leadership & Innovation:
Lead the research, experimentation, and rapid iteration in developing and evaluating advanced data science models for Marketing. This includes pioneering new approaches and refining existing methodologies for Marketing Mix Models (MMM), Customer Lifetime Value (LTV) modelling, and CRM modelling. You will driving innovation in how we build, validate, and deploy models that accurately predict customer behaviour, measure campaign effectiveness, and inform strategic marketing investments, directly contributing to Wise's growth
- Coach,Mentors & Scale:
Lead, mentor, and grow the team building technical capabilities, fostering career development, and promoting knowledge sharing on cutting-edge technologies and methodologies. You will also be responsible for prioritising projects and allocating resources effectively within the data science team to ensure alignment with strategic objectives and timely delivery of impactful solutions.
WHAT YOU’LL BRING
- Technical Expertise:
7+ years hands-on experience. Strong technical foundation with expertise in coding (Python, SQL). You possess deep expertise in lifetime value (LTV) modelling and econometrics / marketing mix modelling, complemented by a strong understanding of statistics, particularly Bayesian reasoning, which enables you to accurately estimate results and know when to deliver actionable insights. Your technical toolkit includes experience with Bayesian approaches to machine learning, neural networks (ideally Py Torch), and a solid grasp of causal inference concepts, including their application with machine learning models. Furthermore, you are adept at navigating a diverse range of model types, confidently selecting between gradient boosting, neural networks, linear regression, or a blend, based on the specific problem and desired outcome.
- Leadership:
2+ years experience leading high-performing data science teams, driving the development of models in Marketing. Demonstrated ability to build, scale, mentor, and retain top technical talent, fostering collaborative and innovative team cultures.
- Domain Expertise:
Experience in marketing operations and strategy with a deep understanding of the customer lifecycle from a marketing perspective. This includes expertise in customer acquisition, retention, engagement strategies, marketing campaign drivers, and the unique data challenges inherent in measuring marketing effectiveness, LTV, MMM, and CRM.
- Communication & Influence:
Excellent communication skills with the ability to translate complex technical concepts into strategic business language and build consensus across diverse stakeholder groups.
- Strategic Ownership & Pragmatism:
Demonstrated ability to proactively identify impactful opportunities, influence business strategy, and drive initiatives to completion. You possess a pragmatic approach, effectively triaging requests and adapting analysis scope to achieve optimal outcomes in a fast-paced environment.
NICE TO HAVE BUT NOT ESSENTIAL
-
An advanced degree (Masters / PhD) in Computer Science, Data Science, Machine Learning, Mathematics/Physics, or related quantitative fields preferred.
-
Experience within Financial Services or Fin Tech
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.
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](https: //wise.jobs/our-mission) and
[what we offer](https: //wise.jobs/what-we-offer).
Required skills
Data science
People management
Marketing analytics
LTV modeling
MMM
CRM modeling
Experimentation
Stakeholder communication
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About Wise

Wise
PublicWISE inspires girls and women to study and build careers in science, technology, engineering and manufacturing.
1-50
Employees
Bradford
Headquarters
$8.0B
Valuation
Reviews
10 reviews
3.8
10 reviews
Work-life balance
3.2
Compensation
4.0
Culture
4.1
Career
3.5
Management
3.7
72%
Recommend to a friend
Pros
Flexible work hours and remote options
Supportive and approachable management
Collaborative environment and teamwork
Cons
High workload and unpredictable demands
Communication issues and lack of direction
Stressful and overwhelming work environment
Salary Ranges
117 data points
Junior/L3
Mid/L4
Senior/L5
Junior/L3 · Data Analyst
1 reports
$91,000
total per year
Base
$70,000
Stock
-
Bonus
-
$91,000
$91,000
Interview experience
4 interviews
Difficulty
2.3
/ 5
Duration
14-28 weeks
Offer rate
50%
Experience
Positive 25%
Neutral 25%
Negative 50%
Interview process
1
Application Review
2
Recruiter Screen
3
Online Interview Round
4
Technical/Role-specific Interview
5
Final Interview
6
Offer Decision
Common questions
Technical Knowledge
Past Experience
Behavioral/STAR
Role-specific Skills
Problem Solving
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