Lead Data Scientist
IN Bengaluru
ResMed
Erfahren Sie mehr über Schlafapnoe und respiratorische Erkrankungen: Ursachen, Symptome & Behandlungsoptionen von ResMed.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 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 our unparalleled store of billion+ nights of sleep data and building sophisticated models to deliver innovative features for our consumers and stakeholders to improve their sleep and sleep related disorders.
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 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.
Let's talk responsibilities:
- Research and development 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.
- Lead, guide and mentor a small and highly skilled team of Data Scientists
- Work closely with other stakeholders from Product Management, Engineering, and other business stakeholders to create impactful, intelligent features and products.
- Collaborate closely with other team members including other Data Scientists, Machine Learning Engineers, and Data Engineers and “own” the end-to-end process.
- Operate with wide authority to develop creative model-based solutions while maintaining high quality and accountability standards.
- Document the model design, experiments, tests, validations, and live metrics and outcomes. You may be asked to write documents for use in the preparation of intellectual property and technical publications.
Let’s talk qualifications and experience:
- Rigorous academic and/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.
- Technical experience in building intelligent data products, prediction models and recommendation engines using ML/AI.
- Proficient with server-side programming in Python/Java.
- Hands-on experience in handling large and distributed datasets on Spark, Hive, etc.
- Strong database skills and experience, including experience with SQL programming.
- Experience with AWS or other cloud-based tools and technologies for ML/AI model development and deployment.
- 6+ years’ industry or academic experience in data science.
- Post-graduate research experience (PhD or equivalent research beyond Masters) in Data Science/Machine Learning or closely related areas such as Computer Science, Operations Research, Applied Statistics, and Biomedical Informatics.
Let’s talk about what you can expect:
- The opportunity to build something meaningful and see a direct positive impact on people’s lives.
- 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.
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! We commit to respond to every applicant.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Bayesian Classification Clustering Computer Science Data Analytics Deep Learning Engineering Feature engineering Java Linear algebra LSTM Machine Learning Mathematics ML models Model design PhD Python Research RNN Spark SQL Statistics Testing Unsupervised Learning XGBoost
Perks/benefits: Career development
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