Data Scientist

Data Scientist

Full-Time 80000 - 98000 £ / year (est.) Home office (partial)
myPOS

At a Glance

  • Tasks: Build and maintain ML models to drive smarter decisions in the Fintech industry.
  • Company: Join myPOS, a leader in making payments simple and accessible for businesses.
  • Benefits: Enjoy competitive salary, health insurance, and unlimited learning opportunities.
  • Other info: We value potential over perfection—apply even if you don’t meet every requirement!
  • Why this job: Make a real impact in the fast-paced world of payments and commerce.
  • Qualifications: 3-5 years of data science experience and strong Python skills required.

The predicted salary is between 80000 - 98000 £ per year.

At myPOS, we’re all about helping businesses grow and get paid. We make payments simple, smart, and accessible for everyone, but we’re more than just payment solutions - myPOS is a partner in growth. From free multicurrency accounts to powerful e-commerce tools, we’re here to support business owners of all sizes and everyone out there who dreams of starting their own business. As we are expanding our team, we’re looking for a Data Scientist to help us make a real difference in the Fintech industry. Ready to join us and shape the future of payments? Let’s make it happen!

About the role: myPOS is building a high-impact Data Science function to power the intelligence layer of one of Europe’s fastest-growing payment and commerce platforms. As a Data Scientist, you will contribute to a focused team working across a rich portfolio of models that drive smarter decisions in Sales, Marketing, Risk, Operations, Product and Technology. You will move fluidly across problem types: from customer lifetime value and churn modelling to fraud scoring and agentic AI workflows.

What you’ll do:

  • Build and maintain ML models across the core portfolio: CLTV, churn prediction, propensity to buy, and Next Most Likely Product (NMLP).
  • Develop fraud detection models including transaction-level classifiers, merchant behaviour anomaly detectors, and new-account risk scorers.
  • Contribute scored model outputs to the Next Best Action (NBA) decisioning layer that selects the optimal action for each merchant across Sales, Marketing, and in-product touchpoints.
  • Support A/B experiments, uplift tests, and multi-armed bandit evaluations to measure the incremental impact of model-driven interventions.
  • Design and implement end-to-end ML pipelines - from data ingestion and feature engineering through to model training, evaluation, and deployment.
  • Monitor deployed models in production: detect performance degradation, data drift, and data quality issues; iterate and document changes proactively.
  • Collaborate with business teams across Sales, Marketing, Risk, Operations, and Product to translate business problems into well-defined data science solutions.
  • Run rigorous experiments and communicate findings clearly to both technical and non-technical stakeholders.
  • Contribute to LLM-powered agentic workflows using tool-use patterns (RAG, function calling, memory) and frameworks such as LangChain or LlamaIndex.
  • Contribute to team documentation: model cards, methodology write-ups, and internal playbooks that help the team scale its practices.

What you bring:

  • 3–5 years of hands-on applied data science, machine learning or statistical modelling experience in a commercial setting, with models shipped and measured in production.
  • Strong proficiency in Python for data science: pandas, numpy, scikit-learn, XGBoost / LightGBM, and at least one deep learning framework (PyTorch or TensorFlow).
  • Solid grounding in supervised and unsupervised learning: classification, regression, clustering, survival analysis, and time-series modelling.
  • Demonstrable experience building at least one of: CLTV, churn, fraud detection, propensity, or uplift models in a production environment.
  • Comfort working with large-scale structured and semi-structured data; proficient in SQL and cloud data warehouses - GCP and BigQuery strongly preferred.
  • Familiarity with ML experiment tracking platforms (MLflow, Weights & Biases) and model serving patterns (REST APIs, batch inference pipelines).
  • Working knowledge of LLM APIs (OpenAI, Anthropic, etc.) and at least one agentic AI framework (LangChain, LlamaIndex, AutoGen, or similar).
  • Understanding of responsible AI: fairness assessment, model explainability methods (SHAP, LIME), bias detection and mitigation strategies.
  • Clear communication - able to distil statistical findings into actionable insights for both technical peers and business stakeholders.

Why you should join myPOS:

  • Annual salary reviews, promotions, and performance bonuses.
  • myPOS Academy and unlimited LinkedIn Learning access.
  • Annual training and development budget.
  • 9% employer pension contribution.
  • Health insurance, dental insurance, and group life assurance.
  • Refer a friend bonus as we know that working with friends is fun.
  • Teambuilding, social activities and networks on a multi-national level.

Who we are: Since 2014 we’ve been all about making payments easier and more accessible for businesses of all shapes and sizes. Whether you’re at the counter, selling online, or on the move, we’ve got businesses covered with smart, accessible and affordable solutions that keep things easy. Our mission? It’s simple. Help businesses get paid by taking advantage of modern tech and innovative ideas, so payment challenges are a thing of the past.

Pro tip: Take it easy about meeting every requirement—this job description is just that, a job description! Even if you don’t tick every box, want you to apply anyway! This is your chance to grow, learn, and build your career with us. We value potential over perfection, and we are all about mutual growth!

myPOS is committed to providing equal employment opportunities. All qualified candidates will be considered for employment without discrimination based on age, ancestry, colour, marital status, national origin, physical or mental disability, medical condition, veteran status, race, religion, sex, sexual orientation, gender identity or expression, or any other characteristic protected by applicable laws, regulations, and ordinances. Your application will be confidentially reviewed in line with the General Data Protection Regulation (GDPR). Personal information will be used solely for the job application and will be stored for a period needed by the application process. Only short-listed candidates will be contacted. Good luck!

Data Scientist employer: myPOS

At myPOS, we pride ourselves on fostering a dynamic and inclusive work culture that prioritises employee growth and development. As a Data Scientist, you'll have access to extensive training resources, including the myPOS Academy and unlimited LinkedIn Learning, alongside competitive benefits such as annual salary reviews and a generous pension contribution. Join us in our mission to revolutionise the Fintech industry while enjoying a collaborative environment that values innovation and teamwork.

myPOS

Contact Details:

myPOS Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Data Scientist

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 myPOS!

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 Data Scientist at myPOS.

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 myPOS.

Apply Directly through Our Website

When you find a suitable opening like Data Scientist at myPOS, 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 Data Scientist

Machine Learning
Statistical Modelling
Python
pandas
numpy
scikit-learn
XGBoost

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 myPOS, 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 myPOS. 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 myPOS

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 myPOS!

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.