Senior Data Science Manager - Marketing in Bristol

Senior Data Science Manager - Marketing in Bristol

Bristol Full-Time 50000 - 65000 £ / year (est.) Home office (partial)
Wise

At a Glance

  • Tasks: Lead a team to develop data models that drive global marketing strategies.
  • Company: Join Wise, a global tech company revolutionising money management.
  • Benefits: Competitive salary, inclusive culture, and opportunities for career growth.
  • Other info: Diverse and inclusive team environment with a focus on innovation.
  • Why this job: Make a real impact on marketing strategies that reach millions worldwide.
  • Qualifications: 7+ years in data science with strong coding skills and leadership experience.

The predicted salary is between 50000 - 65000 £ per year.

hackajob is collaborating with Wise to connect them with exceptional professionals for this role.

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.

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 drive 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 PyTorch), 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 FinTech.

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.

Wise

Contact Details:

Wise Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Senior Data Science Manager - Marketing in Bristol

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Wise!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Science Manager - Marketing at Wise.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Wise.

Apply Directly through Our Website

When you find a suitable opening like Senior Data Science Manager - Marketing at Wise, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Senior Data Science Manager - Marketing in Bristol

Data Science
Python
SQL
Lifetime Value (LTV) Modelling
Marketing Mix Modelling (MMM)
Customer Relationship Management (CRM) Modelling
Bayesian Reasoning

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.