Description

We are seeking a results-driven Data Scientist to lead analytics and metrics development for our healthcare-focused AI product features. You will work with large-scale telemetry data to generate insights, shape product direction, and enhance overall quality. This role requires a strong combination of technical depth, business thinking, and a passion for improving user experiences through data.
 

Key Responsibilities:
 

  • Design and develop KPIs and success metrics tailored to healthcare-related product features and quality.
     
  • Analyze large volumes of structured and unstructured telemetry data using statistical and machine learning techniques.
     
  • Uncover product insights and emerging trends to identify opportunities and guide strategic decisions.
     
  • Effectively communicate findings through data storytelling, visualizations, and presentations for product and executive stakeholders.
     
  • Collaborate with cross-functional teams to embed insights into product development cycles and improve decision-making.
     
  • Operate with speed and agility—overcoming roadblocks and rapidly delivering iterative insights that inform user-facing improvements.

     

Required Qualifications:


 

  • Demonstrated experience in building product metrics, analyzing user behavior trends, and evaluating experimentation results.
     
  • Strong proficiency in Python for data analysis, modeling, and automation.
     
  • Excellent communication and problem-solving skills, with the ability to turn complex data into clear recommendations.
     
  • Experience working with large-scale data pipelines, telemetry, and analytics platforms.

     

Preferred Qualifications:


 

  • Prior experience in product analytics with a focus on healthcare or AI-driven platforms.
     
  • Exposure to prompt engineering and working with large language models (LLMs).
     
  • Experience analyzing conversational and multi-turn unstructured data.
     
  • Familiarity with tools such as SQL, Spark, Databricks, or cloud-based machine learning platforms (e.g., Azure, AWS).
     
  • Domain knowledge in healthcare or regulated industries is a plus

Education

Any Gradute