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Senior Machine Learning Scientist
Teladoc HealthSenior Machine Learning Scientist developing scalable AI systems for Teladoc Health. Collaborating with teams to enhance decision-making through machine learning and data analytics.
Tech Stack
Tools & technologiesPythonSparkSQL
About the role
Key responsibilities & impact- Partner with Product, Engineering, Clinical, Operations, Marketing, and Data Engineering to design, build, deploy, and operate scalable machine learning and AI systems.
- Own the end-to-end machine learning lifecycle: data and feature engineering through deployment, monitoring, experimentation, and continuous improvement.
- Build production ready time series models to predict real time KPIs and optimize decision actions for clinical operations business optimization.
- Propose, evaluate and interpret results for clinical, product and business decision-makers and own outcomes.
- Collaborate closely with peers and stakeholders to distill requirements of problem definitions, product features, and architecture to improve clinical outcomes using insights and models.
- Develop modular, well-tested, production-quality software using Python, Spark and SQL to build scalable data engineering and machine learning pipelines following best practices.
- Ensure robust model lifecycle management through model versioning, MLflow, automated testing, CI/CD, and production monitoring.
- Build and optimize scalable Spark and Databricks workloads, leveraging distributed computing best practices for large-scale data processing and real-time inference.
- Monitor production models and data pipelines for data quality, feature drift, concept drift, latency, reliability, and business performance, proactively identifying and resolving issues.
Requirements
What you’ll need- 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.
Benefits
Comp & perks- Flexible Vacation Policy
- 80 hours of Paid Sick, Safe, and Caregiver Leave annually
- Performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Machine LearningData EngineeringPythonSparkSQLModel DeploymentStatistical AnalysisFeature EngineeringCI/CDModel Monitoring
Soft Skills
CollaborationCommunicationProblem-SolvingStakeholder EngagementAdaptability