Data Scientist AI for Revenue & Churn (Hybrid)

Planet

Galway

Hybrid

EUR 70.000 - 100.000

Vollzeit

Vor 4 Tagen
Sei unter den ersten Bewerbenden

Eine vollständige Bewerbung in einer Minute

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Zusammenfassung

Planet is seeking a Data Scientist to join our AI team in Galway, working cross-functionally with Sales, Marketing, Customer Success, and Finance to build models that reduce churn, surface cross-sell opportunities, and drive revenue visibility.

Own end-to-end analytics, from feature engineering to production deployment, while delivering clear insights to non-technical stakeholders. Hybrid work model with three days in the office.

Qualifikationen

  • 5+ years in applied data science with commercial focus
  • Strong SQL and Python and production-grade code
  • Hands-on Snowflake or equivalent cloud data warehouse
  • Experience deploying models on AWS (SageMaker, Lambda)
  • Solid grounding in statistics, experimentation, and causal inference
  • Track record of shipping models used by business
  • Excellent communication to non-technical audiences

Aufgaben

  • Churn modelling — build, deploy, iterate on churn prediction models
  • Cross-sell & upsell — develop propensity models and next-best-action recommendations
  • Revenue attribution & tracking — design attribution frameworks across marketing channels
  • Experimentation — design and analyse A/B tests and quasi-experiments
  • Productionisation — take models from notebook to production lifecycle
  • Stakeholder partnership — translate business questions into analytical problems

Kenntnisse

SQL
Python
Production-grade code
Snowflake
AWS
Statistics
Communication
Causal inference

Tools

BigQuery
Databricks

Jobbeschreibung

Planet is seeking a Data Scientist to join our AI team in Galway, working cross-functionally with Sales, Marketing, Customer Success, and Finance to build models that reduce churn, surface cross-sell opportunities, and drive revenue visibility.

Own end-to-end analytics, from feature engineering to production deployment, while delivering clear insights to non-technical stakeholders. Hybrid work model with three days in the office.

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