VitalConnect is a leader in wearable biosensor technology for wireless patient monitoring in both hospital and remote patient populations. VitalConnect leverages extensive expertise in biomedical engineering, data analytics, chip design, and mobile and cloud software to create technology that supports decision-making paradigms that achieve better health and economic outcomes. VitalConnect’s products are designed for use in a broad range of inpatient and outpatient settings, such as hospital monitoring, post-discharge care, cardiac monitoring and pharmaceutical solutions. The R&D team at VitalConnect is looking for an experienced Data Scientist to help us expand our product features and functionalities that will have a big impact on patient lives and well-being. As a Data Scientist, you will work closely with the members of the team to help develop data-driven products and machine learning systems that will be crucial to our mission and the success of the company. We are seeking someone with a passion to work on massive amounts of physiological datasets, and to be a part of a growing team that shapes the future of healthcare. If you feel this is you, we'd love to hear from you.
How you'll contribute:
Architect, design, implement and test machine and deep learning algorithms to analyze physiological data from sensors and derive data-driven health insights
Prepare and manage large physiological datasets to run experiments with the goal of optimizing our products.
Work closely with software and firmware engineers to bring your algorithms to production
Assess the effectiveness and accuracy of new data sources and data gathering techniques
Conduct exploratory data analysis and visualization
Contribute to the development and deployment of reusable data science tools at scale
Benchmark and validate the performance of models and algorithmic techniques
Extract novel insights from physiological datasets to improve outcomes and economics of care
Contribute to corporate patent portfolio and technical publications.
Who You Are
2+ years of experience in applying scalable machine and deep learning to solving data science problems in real world environment
Strong hands-on expertise with a variety of machine learning techniques (supervised/unsupervised, clustering, decision tree learning, neural networks, etc.) and their real-world advantages/drawbacks/tuning techniques
Excellent software development skills with python packages such as: numpy, scipy, pandas, and scikit-learn
Experience with tensorflow or pytorch is strongly desired
Knowledge of signal processing is an advantage
Bachelors or advanced degree in a quantitative discipline (Computer Science, Mathematics, Electrical Engineering, Bioengineering, Information Systems, Statistics, or related fields); data science concentration is a plus.
How To Stand Out From The Crowd
Top score in data science competitions and/or published work in top tier journals and conferences
Have experience developing and validating time-series ML/DL algorithms
Experience with leading data science projects from conception to production