Teladoc Health is looking to create data products, analyses, and machine learning models to predict and explain member clinical behavior and outcomes across multiple conditions, aiming to improve the measurement and prediction of member experience and clinical risk.
Requirements
- Advanced understand of statistics and machine learning (including inference, causal modeling, supervised machine learning.
- 3+ years experience programming data pipelines, statistical analyses, and machine learning algorithms.
- Experience with engineering cadence, habits and tools (github, jira, dags(Jenkins/Airflow/etc), docker)
Responsibilities
- Creating data products, analyses and machine learning models that predict and explain member clinical behavior and outcomes across multiple conditions.
- Creation of new algorithms that improve Teladoc Health’s ability to measure and predict member experience and clinical risk.
- Characterizing clinical outcome measures for internal product decisions and for external product marketing
- Reporting on clinical performance to external entities such as the CDC and the AADE.
- Client reporting and billing analysis in areas of subject matter expertise
- Building personalized data products that enable human decision making and power aspects of Teladoc Health’s products directly
Other
- Bachelor’s degree in Information Systems, Computer Science, Software Engineering, or related field. In lieu of a bachelor’s degree, equivalent combination of education and experience is accepted
- 5+ years experience as a Clinical Data Scientist in Healthcare
- Strong problem-solving skills and the ability to translate vague requirements into impactful data science projects efficiently.
- Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.
- This position is eligible for a performance bonus and benefits (subject to eligibility requirements)
