🛠 Tech Stack

💼 About This Role

You'll build, deploy, and maintain data science models that directly improve revenue outcomes and customer experience. You'll work end-to-end from defining problems with commercial stakeholders to production deployment with the Data Engineering team. This role offers high autonomy and ownership of impactful projects.

🎯 What You'll Do

• Partner with Sales, RevOps, CS, Marketing to translate commercial questions into model-ready datasets.
• Build and iterate on predictive models (health scoring, intent scoring) with rigorous validation.
• Deploy models into production in collaboration with Data Engineering.
• Maintain and improve existing models: performance monitoring, retraining, drift detection.

📋 Requirements

• Several years of industry experience building statistical/ML models end-to-end.
• Strong foundations in applied machine learning and statistics.
• Production mindset with experience monitoring and retraining deployed models.
• Strong SQL and Python skills with data wrangling and feature engineering.

✨ Nice to Have

• Experience on commercial/goto-market problems (lead scoring, churn, expansion).
• Experience with modern data stacks (Snowflake, dbt, Airflow) and production ML patterns.
• Experience designing model outputs for commercial workflows (dashboards, CRM signals).

🎁 Benefits & Perks

• 🚀 Ownership of end-to-end projects from definition to production.
• 🏢 High autonomy with no Jira or ticket conveyor belt.
• 🤝 Close collaboration with commercial stakeholders and Data Engineering.
• 📈 Work on impactful problems at the intersection of product usage and revenue.