Data Scientist

myPOS AD; Greater London; On-site; GBP 60,000 - 80,000; Full time

Benefits offered by this job

Annual salary reviews

Unlimited LinkedIn Learning access

9% employer pension contribution

Health insurance

Job summary

myPOS, based in Greater London, is seeking an experienced Data Scientist to support our rapidly expanding payment solutions. You will build and maintain machine learning models, optimize decision-making processes, and collaborate with diverse teams to drive impactful projects.

The ideal candidate will have 3-5 years of applied data science experience, proficiency in Python, and a solid understanding of machine learning methodologies. Join us in transforming the future of payments!

Qualifications

• 3–5 years of hands-on applied data science experience in a commercial setting.
• Experience with large-scale structured and semi-structured data.
• Familiarity with ML experiment tracking platforms.

Responsibilities

• Build and maintain ML models across core portfolio.
• Develop fraud detection models.
• Contribute to A/B experiments and decisioning layers.

Skills

Python for data science

Machine learning

SQL

Data analysis

Communication

Tools

pandas

scikit-learn

GCP

Job description

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 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!