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

ATS Keywords

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Hard Skills

SQLPythonmachine learningmodel productionizationevaluation frameworksmodel performance monitoringchurn analysissegmentationLTV modelingrecommender systems

Soft Skills

strong communicationsimplifying technical concepts

Tools & Technologies

AI coding toolsproduction systemsAPIsinternal toolsML infrastructure

Industry Keywords

loyalty analyticsCRMretail analyticsAI agentsbilingual (French/English)

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.