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Senior Data Scientist
  • Python
  • Spark
  • SQL
  • Java
  • Machine Learning
  • Big Data
  • Data Analysis
  • Excel
  • Database
  • Data Mining
  • Data Visualization
  • Hadoop
San Diego, CA 92123
113 days ago

Digital Health Technology team powers digital experiences and engagement to enhance the lives of millions of people every day through connected care. We build, deliver and manage a portfolio of data management platforms and mobile offerings in support of our core businesses. We thrive on simple and elegant architecture and agility. You’ll be immersed in a dynamic high-growth environment and empowered to excel, take informed risks, and drive ingenuity across the enterprise.

Let's talk about the team and you:

The Senior Data Scientist will undertake applied research and development in the areas of data science and biomedical informatics, and outcomes research, using the latest technologies in machine learning and distributed computing. The platform and algorithms developed may be used in a range of diagnostic and therapeutic applications, such as sleep disorder breathing, chronic obstructive pulmonary disorder, and other respiratory disorders, as well as co-morbidities such as congestive heart failure and diabetes and chronic disease management.

Let's talk responsibilities:

The Advanced Analytics team is focused on developing analytics solutions that will enable a data-driven approach to addressing business questions. This role will collaborate with the global Analytics team in support of achieving global and regional business goals.

  • Research, customization, and development of statistical and machine learning algorithms to meet complex project requirements; tasks include defining hypotheses, executing necessary tests and experiments, evaluating, tuning and optimizing algorithms and methods to specific situations.
  • Analysis of big data for data-driven solution validation, evaluation and technology innovation.
  • Optimize data analysis processes and systems for better efficiency and maintainability.
  • Leading sub-functional and small project teams.
  • Mentoring and training more junior team members and serving as a best-practice resource for statistics and machine learning.
  • Writing of documents that clearly explain how algorithms should be implemented, verified and validated.
  • Writing documents for use in the preparation of intellectual property and technical publications.
  • Monitoring the literature of interest and industrial development trends, broadly in the areas of data analysis and machine learning.
  • Understanding regulatory requirements, such as those mandated by the FDA.
  • Working within the ResMed Quality system, standards and maintaining training requirements.
  • Being ever mindful of the requirements of the wider market and ResMed stakeholders.
  • Promoting safe working environment within OH&S guidelines

Let's talk qualifications and experience:

  • Expert in statistical analysis methods, including analysis of variance, regression, time series analysis, survival analysis, etc.
  • Extensive knowledge in machine learning fundamental theories and data mining technologies.
  • Leadership and hands on experience with development of data analytics systems, including data exploration/crawling, feature engineering, model building, performance evaluation, and online deployment of models.
  • Proficient with server-side programming in Python/Java.
  • Hands-on experience in handling large and distributed datasets on Hadoop, Spark, Hive, Pig or Storm, etc.
  • Strong database skills and experience, including experience with SQL programming.
  • Knowledge in big data technologies including cloud computing/distributed computing, data fusion, and data visualization.
  • Experience in R programming.
  • A background in or exposure to biomedical engineering, outcomes research, medical science or physiology.
  • Good technical writing and presentation skills.
  • Optimisation of algorithm complexity vs. accuracy vs. implementation cost.
  • Implementing robust software for use in research programs with a minimum of review and other formal process
  • Degree in Computer Science, Engineering, Statistics, Applied Mathmatics, or related fields.
  • Minimal 6 years’ industry or academic experience in data science.


  • Post-graduate research experience (Masters or PhD) in a field encompassing Data Science, Applied Statistics, Biomedical Informatics, or Outcomes Research.
  • Relevant industry experience would be favourably considered.


Joining us is more than saying “yes” to making the world a healthier place. It’s discovering a career that’s challenging, supportive and inspiring. Where a culture driven by excellence helps you not only meet your goals, but also create new ones. We focus on creating a diverse and inclusive culture, encouraging individual expression in the workplace and thrive on the innovative ideas this generates. If this sounds like the workplace for you, apply now!

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