Senior Machine Learning Scientist
$150,000–$175,000 year
RemoteUnited States
Job Summary
Build production-ready time series models to predict real-time KPIs and manage provider networks for clinical operations optimization. Design, develop, and operate scalable machine learning and AI systems, including data transformation, feature pipelines, model training, evaluation, and monitoring across batch and real-time environments. Ensure robust lifecycle management through versioning, automated testing, CI/CD, and production observability using Python, Spark, and SQL. Integrate Large Language Models and retrieval-augmented generation to solve business problems while measuring outcomes and iterating on production performance. This role sits within the Data Science team at Teladoc Health, empowering you to improve member and provider experiences on the platform.
Required Qualifications
- 8+ years of experience as a Machine Learning Scientist, Data Scientist or in a similar role within SaaS or consumer technology companies
- A Master's degree or higher in computer science, operations research, machine learning, information systems, engineering, or a related field
- Demonstrated depth of experience developing clean, robust, and reusable production-quality code using Python, Spark, and SQL
- Extensive experience designing, building and operating production machine learning systems, including scalable software, distributed data processing, reusable feature engineering pipelines, model deployment, monitoring and continuous improvement
- Strong understanding of statistical modeling, machine learning algorithms, experimentation, model evaluation, forecasting, and explainability techniques, with the ability to select appropriate approaches based on business and technical constraints
- Excellent data analysis skills and bias to deliver, measure and iterate using experimentation and statistical analysis
- Strong system design skills with the ability to architect scalable, maintainable, and observable machine learning solutions
- Ability to translate machine learning solutions into measurable business outcomes and effectively communicate technical decisions, tradeoffs, and expected value to both technical and business stakeholders
- Hands-on experience with modern data and ML platforms such as Databricks, MLflow, Delta Lake, Airflow, Terraform, or equivalent cloud-native technologies
- Experience building AI-powered applications using Large Language Models (LLMs), embeddings, vector databases, retrieval-augmented generation (RAG), agentic workflows, or equivalent AI technologies
- Experience applying machine learning, forecasting, optimization, or decision science techniques to large-scale operational, logistics, marketplace, or network optimization problems
- Experience working with healthcare data (e.g., claims or EHR)
- Great active listening skills to infer product/business needs and underlying context
- Ability to collaborate effectively with peers, and respect for member privacy
- Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future
Desired Qualifications
- Bonus Qualifications Hands-on experience with modern data and ML platforms such as Databricks, MLflow, Delta Lake, Airflow, Terraform, or equivalent cloud-native technologies
- Experience building AI-powered applications using Large Language Models (LLMs), embeddings, vector databases, retrieval-augmented generation (RAG), agentic workflows, or equivalent AI technologies is highly desirable
- Experience applying machine learning, forecasting, optimization, or decision science techniques to large-scale operational, logistics, marketplace, or network optimization problems
- Experience working with healthcare data (e.g., claims or EHR) is a plus
- Great active listening skills to infer product/business needs and underlying context
- Ability to collaborate effectively with peers, and respect for member privacy
Hiring someone like this?
Get your role in front of qualified candidates on Sorce.