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sql python dbt scikit-learn xgboost
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πŸ“‹ Description

  • Own the end-to-end lifecycle of ML models powering product experiences, coverage recommenders
  • Engineer features, prototype experiments, and ship iterative model improvements to production
  • Work with engineering and PMs to define how model scores are consumed in real-time product surfaces

🎯 Requirements

  • 5+ years in data science or ML at established firms or high-growth tech
  • Strong command of supervised learning and recommendation systems; you've shipped production models
  • Proficiency in Python (pymc, scikit-learn, XGBoost/LightGBM) and SQL
  • Hands-on Bayesian experience: prior elicitation, posterior inference, and experiment design
  • Experience deploying production models integrated with consumer-facing products
  • Strong communication skills; able to translate model behavior and uncertainty into stakeholder

🎁 Benefits

  • Compensation details listed in US role postings reflect the base salary only and do not include
  • Further details of US benefits available at https://www.ethoslife.com/careers/
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