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Paystone

Data Scientist

Paystone

Remote Data Scientist at Paystone building machine learning models that impact customer experiences. Collaborating with cross-functional teams to turn data into actionable insights and systems.

Posted 6/10/2026full-timeRemote • 🇬🇧 United KingdomMid-LevelSeniorWebsite

ATS Keywords

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Hard Skills
SQLPythonmachine learningmodel productionizationsegmentationchurn analysisLTV modelingrecommendation systemsmodel evaluation frameworksmodel performance monitoring
Soft Skills
strong communicationsimplifying technical conceptscollaborationproblem-solvingiteration cycles management
Tools & Technologies
AI coding toolsAPIsproduct telemetryuser feedback systemsinternal toolsML infrastructure
Industry Keywords
data scienceapplied scienceML engineeringloyalty analyticsCRMretail analyticsLLMAI agentsagentic workflows

Tech Stack

Tools & technologies
PythonSQL

About the role

Key responsibilities & impact
  • Partner with Product and BI to turn business goals into well-scoped ML problems with clear success criteria and guardrails.
  • Build and productionize models for segmentation, churn, LTV, and recommendations.
  • Design evaluation frameworks including offline benchmarks and online feedback loops to ensure models are measured, not assumed.
  • Collaborate with Engineering on production design considerations like latency, payload structure, fallbacks, and failure modes.
  • Monitor model performance over time, detect drift, and own retraining and iteration cycles.
  • Use product telemetry and user feedback to drive continuous model and feature improvements.
  • Work alongside AI coding agents to accelerate development (pipelines, tests, refactoring, exploration) while maintaining human oversight.
  • Communicate results, trade-offs, and recommendations clearly across technical and non-technical teams.

Requirements

What you’ll need
  • 5+ years as a Data Scientist, Applied Scientist, or ML Engineer.
  • Strong SQL and Python skills with production ML experience.
  • Experience with churn, segmentation, LTV, or recommender systems.
  • Comfortable working with production systems and APIs.
  • Familiar with AI coding tools and agentic workflows.
  • Strong communicator who can simplify technical concepts.
  • Nice to Have: Experience in loyalty, CRM, or retail analytics; LLM or AI agent experience; Building internal tools or ML infrastructure; French/English bilingual.

Benefits

Comp & perks
  • Flexibility: People-first approach focused on outcomes, not location or hours.
  • Collaboration: Partner closely with Product, Engineering, and BI in a fast-moving, supportive environment.