At a Glance
- Tasks: Lead data science projects to personalise customer experiences and enhance product recommendations.
- Company: Join Wise, a global tech company revolutionising money management.
- Benefits: Enjoy flexible working, stock options, generous leave, and a fun work environment.
- Other info: Diverse and inclusive culture that values unique backgrounds and experiences.
- Why this job: Make a real impact on millions of customers while developing your skills in a dynamic team.
- Qualifications: Expertise in Python, SQL, and machine learning model deployment required.
The predicted salary is between 90500 - 127000 £ per year.
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.
We’re looking for a Lead Data Scientist to join our growing CRM Team in London. This role will give you the opportunity to have a direct impact on how millions of Wise customers find the perfect products for their needs at exactly the right moment, while evolving your skills by owning production-level machine learning projects from end to end. This is an individual-contributor (IC) role — you'll own technical direction and delivery, not people management.
Your mission: Wise has pioneered new ways for people to move and manage money across borders. Once someone joins Wise, our CRM tribe makes sure every customer discovers the products that actually help them — a card if they travel, multi-currency balances if they hold FX, a current account if they use Wise for day to day banking. Your mission is to develop a learning system that recommends the right product, to the right customer, at the right moment — and measures whether it worked.
Here’s how you’ll be contributing to CRM:
- You will design and maintain the data pipelines and ML-ready tables that power feature generation, model training, inference and impact measurement – with clear ownership of data quality, reproducibility and training-serving consistency.
- You will help the CRM tribe find the biggest opportunities for growth and personalisation across the customer lifecycle — onboarding, engagement, activation, retention.
- You will own predictive/uplift or recommendation models that decide what to recommend and who to talk to, powering personalised CRM journeys end-to-end.
- You will model customer behaviour, product-usage patterns and CRM engagement (email/push clicks) to identify who's likely to churn, who's ready for their next product, and measure how much value a campaign actually created.
- You will partner closely with Data Analysts, Data Engineers and CRM Campaign Managers, translating models into levers they can use.
Your average day will include building or maintaining production models, running experiments, evaluating new ideas, and communicating what models can (and cannot) tell us about how and why CRM drives growth.
This role will give you the opportunity to:
- Have a direct impact — you will closely partner with the CRM and CRM Analytics team to help ship models that reach every Wise customer through CRM campaigns and personalisation surfaces.
- Own the problems worth solving — you will not just be handed a backlog. You will form strong opinions on where DS creates the most value and convince the people around you to do what is necessary to help.
- Work autonomously - we believe people are most empowered when they can act autonomously. So rather than telling you what to do, you’ll work with your team to create a vision of your own.
- Be part of a diverse team - You will work in a team of Data scientists, Analysts, Engineers and CRM Managers.
- Be part of our mission to make money without borders the new normal.
About you:
- You have expert knowledge of Python and are able to make and justify design decisions in your code (packaging, testing, config-driven pipelines).
- You have expert knowledge of SQL and can write, debug and optimise complex queries against a warehouse.
- You have hands‑on experience shipping and operating predictive ML models or recommendation systems in production (classification / propensity / churn / next‑best‑action) — end‑to‑end from feature pipelines (SQL or feature store) and ML‑ready training / scoring datasets, through model registries, batch or real‑time inference, and monitoring — with sound data‑modelling practices and data‑quality checks along the way.
- You know when to reach for gradient boosting, neural networks, linear models, or a blend.
- You have designed and analysed A/B tests end‑to‑end — power calculations, choosing the right unit of randomisation, guardrail metrics, interpreting inconclusive results.
- You have a proficient understanding of statistics — sample size, variance, multiple‑comparisons, Bayesian reasoning.
- You know how to measure the incremental impact of ML models and CRM interventions end‑to‑end — defining success and guardrail metrics, designing and powering A/B tests, choosing the right unit of randomisation, quantifying uncertainty, accounting for multiple comparisons, and interpreting inconclusive results to inform business decisions.
- You take end‑to‑end ownership with a structured, data‑driven approach — cutting through vagueness to frame the business problem, prioritising the value you can add, and defining precisely where and how a model fits into the stack.
- You communicate effectively with any audience — translating model choices, uncertainty and trade‑offs into decisions non‑DS teams (Product, Marketing, CRM Ops, Compliance) can act on, and visualising data clearly along the way.
- You operate beyond your direct team — shaping design decisions on the product or engineering side, mentoring other DS and analysts, spawning and running cross‑functional projects through to delivery, educating the wider company on what DS can do, and keeping current with developments in your areas (recommenders, uplift, causal inference).
Some extra skills that are great (but not essential):
- You have hands‑on experience with sequential and/or deep‑learning recommender models — two‑tower architectures, transformer‑based rankers, or sequence embeddings.
- You have experience with uplift modelling and conditional average treatment effects for personalisation.
- You are familiar with dbt, Snowflake, AWS (S3, SageMaker), Airflow, and Trino / data lake stacks.
- You have prior CRM / marketing / e‑commerce ML experience — customer lifecycle segmentation, campaign attribution, contact strategy optimisation.
Office: London, UK
Salary range: GBP 90.5K-127K yearly gross based on experience and interview outcomes.
Key benefits:
- Flexible working - whether it’s working from home, school plays or life admin we get that flexibility is essential and you’re trusted to do the right thing and be responsible.
- Stock options in a profitable company.
- Relocation support.
- Generous parental leave.
- Pension scheme.
- Paid sabbatical.
- Loads of development opportunities.
- Sports and wellbeing compensation.
- A fun work environment with social activities and events.
- The opportunity to work with super smart, curious people.
We’re people without borders — without judgement or prejudice, too. We want to work with the best people, no matter their background. So if you’re passionate about learning new things and keen to join our mission, you’ll fit right in. Also, qualifications aren’t that important to us. If you’ve got great experience, and you’re great at articulating your thinking, we’d like to hear from you. And because we believe that diverse teams build better products, we’d especially love to hear from you if you’re from an under‑represented demographic.
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.
Lead Data Scientist - Personalisation/CRM employer: Wise group
Wise is an exceptional employer that fosters a collaborative and innovative work culture in the heart of London. With a strong emphasis on employee growth, you will have the opportunity to lead a talented team while developing your skills in a dynamic environment. The company offers competitive benefits and a commitment to work-life balance, making it a rewarding place for those looking to make a meaningful impact in the KYC verification space.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Scientist - Personalisation/CRM
✨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 group!
✨Show Off Your Projects
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✨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 group.
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Scientist - Personalisation/CRM at Wise group, 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 Lead Data Scientist - Personalisation/CRM
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 group, 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 group. 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 group
✨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 group!
✨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.