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Let’s talk about the team and you:
The Data Science and AI/ML team collaborates across the organization to identify, develop and deliver Artificial Intelligence (AI) and Machine Learning (ML) powered software solutions that improve patient outcomes, delight our partners and customers, and improve the way we do business in an “AI First” fashion. On any given day, the team could be working on building sophisticated models to delivering personalized recommendations to patients to improve their sleep, identify optimal equipment and settings using our unparalleled store of billion+ nights of sleep data, proactively identify other health risk factors, or help optimize complex, global supply chain operations.
The Lead Data Scientist will develop model-based solutions in multiple areas of business interest to ResMed, using the latest technologies in machine learning and cloud computing. The platform and algorithms developed may be used in a range of use cases in personalizing the patient journey from disease identification through treatment and support in order to deliver the best health outcomes. Examples could include models for diagnostic and therapeutic applications in sleep disorder breathing, chronic obstructive pulmonary disorder, and other respiratory disorders, as well as co-morbidities and chronic disease management.
This role is based in San Diego, CA. If you are a U.S based applicant open to relocating to San Diego, please include that information in your resume.
Let’s talk responsibilities:
- You will research, customize when necessary, and develop of statistical and machine learning algorithms to meet complex product requirements. Your tasks will include defining hypotheses, executing necessary tests and experiments, evaluate, tune and optimize algorithms and methods always with an eye towards implementation ease, scalability, and robustness in a live environment.
- You will work closely with other stakeholders from Product Management, Engineering, and other business stakeholders to create impactful, intelligent features and products.
- You will collaborate closely with other team members including other Data Scientists, Machine Learning Engineers, and Data Engineers and “own” the end to end process.
- You will be given wide authority to develop creative model-based solutions but will also be held to high quality and accountability standards.
- You will mentor and train more junior team members and serve as ago-to expert in your area of statistics and machine learning.
- You will thoroughly and diligently document the model design, experiments, tests, validations, and live metrics and outcomes, typically on Confluence. You may be asked to write documents for use in the preparation of intellectual property and technical publications.
Let’s Talk Qualifications and Experience:
- 8+ years’ industry or academic experience in Data Science
- Post-graduate research experience (PhD) in Data Science/Machine Learning or closely related areas such as Computer Science, Operations Research, Applied Statistics, and Biomedical Informatics.
- Rigorous academic or experiential knowledge of the mathematical essentials for Data Science, including key concepts in probability and statistics, optimization, time series analysis, linear algebra and discrete math. Sampling and estimation, Bayesian analysis, hypothesis testing, uncertainty estimation, stochastic methods, and graphical methods are particularly important to know.
- Deep grounding in machine learning techniques including regression methods (linear, logistic, lasso, support vector, etc.), classification (tree-based models such as XGBoost and Random Forest, Neural Networks, Deep Learning – CNN, RNN, LSTM, etc.), as well as knowledge of clustering and unsupervised learning, time series forecasting and optimization methods.
- Solid foundation 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, etc.
- Strong database skills and experience, including experience with SQL programming.
- Experience with AWS or other cloud-based tools and technologies for data pipelining, model development and deployment
Let’s talk about what you can expect:
- A supportive environment that focuses on people development and best practices
- Opportunity to design, influence and be innovative
- Work with global teams and share new ideas
- Be supported both inside and outside of the work environment
- The opportunity to build something meaningful and see a direct positive impact on people’s lives