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Sr. Manager, Data Science

LinkedIn Resmed San Diego, CA
Mid-Senior level Posted April 1, 2026 Job link
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Requirements
  • 8+ years of industry experience in Data Science, Machine Learning Engineering, or related fields.
  • Proven experience managing and leading data science or AI teams, including mentoring junior members and developing team processes.
  • Experience in productionization of AI models and collaboration with engineering for deployment and support.
  • Excellent communication and stakeholder management skills.
  • Proven ability to work across cross-functional teams and drive consensus on technical strategies and business priorities.
  • Demonstrated expertise in model development, deployment, and performance evaluation for production-grade AI solutions.
  • Strong foundation in probability, statistics, computer science, time series analysis, linear algebra, and discrete math.
  • Extensive, practical experience applying advanced AI and machine learning methods—such as NLP, time-series analysis, computer vision, recommender systems, and reinforcement learning—using common algorithms, with a strong understanding of their real-world trade-offs in production settings.
  • Extensive experience building and managing ETL pipelines and data workflows to handle large, complex structured and unstructured datasets, enabling their effective use in AI algorithm development.
  • Previous hands-on experience in Python with a strong track record of developing, deploying, and monitoring machine learning models in cloud-based production environments, emphasizing robust evaluation and operational effectiveness.
Preferred Skills
  • Demonstrated expertise in model development, deployment, and performance evaluation for production-grade AI solutions.
  • Strong foundation in probability, statistics, computer science, time series analysis, linear algebra, and discrete math.
  • Extensive, practical experience applying advanced AI and machine learning methods—such as NLP, time-series analysis, computer vision, recommender systems, and reinforcement learning—using common algorithms, with a strong understanding of their real-world trade-offs in production settings.
  • Extensive experience building and managing ETL pipelines and data workflows to handle large, complex structured and unstructured datasets, enabling their effective use in AI algorithm development.
  • Previous hands-on experience in Python with a strong track record of developing, deploying, and monitoring machine learning models in cloud-based production environments, emphasizing robust evaluation and operational effectiveness.
Education
  • (Not required) – Master’s or PhD in Data Science, Machine Learning, Computer Science, Operations Research, Applied Statistics, Biomedical Informatics, or closely related disciplines.