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Paystone

Data Scientist

Paystone

Data Scientist developing and shipping machine learning models that enhance customer experiences for Paystone. Collaborating with cross-functional teams to drive data-based solutions.

Posted 6/6/2026full-timeRemote • 🇮🇩 IndonesiaMid-LevelSeniorWebsite

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.

ATS Keywords

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Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
SQLPythonmachine learningmodel productionizationevaluation frameworksmodel performance monitoringchurn analysissegmentationLTV modelingrecommender systems
Soft Skills
strong communicationsimplifying technical concepts