About Sofía

At Sofia we want to change the way millions of people take care of their health by offering a health plan that is more complete, simpler to understand, and closer to anyone who wants to live a healthier life. We want to build a thriving community that deeply changes the way the health system works.

About the role

As a Data Scientist at Sofía, you will be positioned to significantly impact the lives of millions of people and you will be continuously exposed to strategic discussions and decisions.

Responsibilities

• Use qualitative, analytical, and predictive methods to understand how our Soci@s can improve their health while engaging with our product in a meaningful way.
• Discover, understand and structure different data sources into clean data models that unlock self-service analytics.
• Define, implement, and monitor key performance metrics for all teams across Sofía.
• Empower our operation with self-service tools (dashboards, data cubes, etc.) to better understand and serve our Soci@s.
• Work closely with Product, Engineering & Marketing/Growth teams to help them shape their roadmap and strategic priorities.
• Design experiments to evaluate initiatives that are live and identify areas for improvement.

What We're looking for

• 3+years of work experience in a quantitative analytical role.
• Proficiency with statistical software (e.g., R, Python), database languages (e.g., SQL), and code versioning tools (e.g., Git).
• Proven experience articulating, translating, and solving business problems through data.
• Self-direction and eagerness to collaborate with other teams (Product, Engineering, Maketing/Growth).
• Effective written, verbal and visual communication skills.
• Willingness to both teach others and learn new techniques.

Bonus points:

• Knowledge of health care, health economics, or health insurance.
• Applied experience deploying machine learning models into production.
• Experience extracting and manipulating large datasets with tools like Presto or Spark.
• Postgraduate degree in a quantitative discipline (e.g., Mathematics, Computer Science, Statistics, Economics, Actuary, Operations Research, Industrial Engineering, etc.).