Data Scientist

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We are looking for a Data Scientist to help shape the future of payments by building data-driven solutions that improve fraud detection, streamline merchant onboarding, enhance customer experiences, and support smarter decision-making across the business. In this role, you’ll work closely with product, engineering, and operations teams to uncover insights from complex datasets and develop predictive models that drive measurable impact.

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• Build and deploy machine learning models for fraud detection, transaction scoring, and behavioural insights.
  
• Develop statistical models and forecasting tools that improve operational efficiency and reduce risk.
  
• Apply NLP, anomaly detection, clustering, and other advanced techniques to extract value from payments and customer data.
  
• Conduct exploratory data analysis (EDA) to surface trends, anomalies, and optimisation opportunities.
  
• Turn complex datasets into clear, actionable insights through dashboards, visualisations, and reporting.
  
• Partner with stakeholders to define KPIs and measure product performance.
  
• Work alongside data engineers to design scalable data pipelines and ensure high-quality, reliable datasets.
  
• Support integration of structured and unstructured data sources across the wider organisation.
  
• Contribute to the evolution of data lakes, warehouses, and real-time analytics environments.
  
• Collaborate with Product, Risk, Compliance, and Operations teams to align analytics with business goals.
  
• Present insights and recommendations to both technical and non-technical audiences.
  
• Support experimentation initiatives, including A/B tests and data-driven product development.
  
• Ensure all data usage meets internal governance standards and industry regulations (GDPR, PCI-DSS).
  
• Maintain clear documentation of models, methodologies, and data sources for auditability and reproducibility.
  

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• Proven experience as a Data Scientist, ideally within payments, fintech, or large-scale analytics environments.
  
• Strong skills in Python, R, SQL, and data science toolkits (e.g., scikit-learn, pandas, TensorFlow).
  
• Hands‑on experience with cloud services (AWS, Azure, GCP) and big data frameworks (Spark, Databricks).
  
• Deep understanding of statistical modelling, machine learning techniques, and data visualisation best practices.
  
• Excellent communication skills and the ability to work effectively with cross‑functional teams.
  

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• Seniority level: Entry level
  
• Employment type: Full‑time
  
• Job function: Information Technology
  
• Industries: Technology, Information and Internet
  
• Location: Northampton, England, United Kingdom