Overview
Project Brief We are driving strategic AI initiatives to transform user retention and engagement for a massive data platform serving the MarTech and publishing industries. We need a Data Scientist to take ownership of a Subscriber Churn prediction model and enhance AI Content Tagging products already live in production. You will navigate complex relational schemas with over 700 tables to build high-impact models that solve real-world business problems.
What You Will Do
- Optimize Churn Models: Evaluate the existing v1 churn model and decide whether to advance or redirect it to maximize accuracy.
- Scale AI Products: Identify and implement improvements for an active AI Content Tagging product to expand its capabilities.
- Strategic Roadmap Delivery: Contribute to initiatives like Smart Pricing recommendations, Send Time Optimization, and Bot Monitoring Agents.
- Data Partnership: Collaborate with internal teams to understand data definitions and translate business requirements into technical solutions.
- Complex Data Navigation:



Explore and clean inconsistent datasets within large-scale relational schemas.

Must-Haves
- Advanced SQL & Python: Strong proficiency in SQL (SQL Server) and Python for data science, including pandas and scikit-learn.
- Cloud Data Platforms: Professional experience with Snowflake.
- Cloud Infrastructure: Experience working within AWS environments.
- Machine Learning Deployment: Proven experience building and deploying predictive models, specifically Churn Prediction or Propensity Scoring.
- Data Dexterity: Ability to work with complex relational schemas and adapt to variable data availability across different clients.
- English Fluency: Advanced level for seamless technical and functional communication.
- Independent Execution: Ability to work autonomously within an established AI Pod.

Nice to Have
- NLP & LLMs: Experience with content classification, LLM context injection, and structuring data for agent consumption.
- Industry Dom

📌 Data Scientist Ssr (Argentina)
🏢 OneSeven Tech (OST)
📍 Argentina