IT & Software

Data Scientist - Payment Success

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London · Greater London · United Kingdom

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Overview

In this role you will partner with merchants to shape payments strategies, perform in-depth data analysis, and run experiments (including ML-driven solutions) to boost performance. You will build automation to monitor merchant metrics, quantify impact, and support cross-functional product development. You’ll elevate awareness of merchant services at executive levels and foster a culture of learning across teams. This is a fast-paced, data-driven environment at a global fintech scale with a strong focus on merchant experience and revenue impact.

Pay / Benefits
  • hybrid working model (3 days in the office)
  • recognition for impact
  • growth opportunities
  • collaborative culture
  • inclusive environment
  • work that makes a difference
Responsibilities
  • Provide expert guidance on merchant payments strategies and optimization
  • Perform exploratory data analysis to uncover insights and anomalies
  • Run experiments and A/B tests, including ML-based solutions, to improve performance
  • Develop automation tools to monitor and optimize merchants’ performance
  • Measure impact of solutions on merchant performance and revenue, informing ROI
  • Collaborate with cross-functional teams to enhance merchant experience and feed product requirements
  • Increase internal awareness of merchant services among executives and stakeholders
  • Foster cross-team learning and knowledge sharing
Key requirements
  • 3+ years in an analytical role in Fintech or Consultancy
  • Experience as Payment Analyst/Expert is a strong advantage
  • Data-driven approach with clear success metrics
  • SQL and Python to extract and analyze large data from a Data Warehouse
  • Knowledge of major e-commerce and payments technologies and trends
  • Customer-driven with ability to build robust relationships with assigned customers
  • customer-centric mindset
  • cross-functional collaboration
  • strong communication and relationship-building
  • SQL
  • Python
  • data warehouse querying/analysis

Reference: WJ-747_31177463 · Posted 01 Nov 2026, 12:08 PM

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