Job Listing
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| Job ID: 13948504 |
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| Job Location: |
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Telecommute (See 'Help' at the top or bottom of page for definition.)
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| How to Apply: | To see employer contact information, log in or register. |
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| Job Title: | Sr. AI/Data Science Engineer |
| Work Type: | Work Days: Weekdays, Work Vary: No , Shift: First (Day), Hours Per Week: 40, Work Type: Regular |
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| Salary Offered: | $129,200.00 - $193,200.00 Yearly |
| Benefits: | Unspecified. |
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| Physical Required: | Unspecified |
| Drug Testing Required: | Unspecified |
| Education Required: | Bachelor's Degree |
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| Experience Required: | 60 Months |
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| Required Skills: | Requires a Master’s degree in Computer Science, Electrical and Computer Engineering, Applied Mathematics, Software Engineering, or a closely related field, and 2 years of experience as a data engineer, data scientist, software engineer, or related occupation, or a Bachelor’s degree in Computer Science, Electrical and Computer Engineering, Applied Mathematics, Software Engineering, or a closely related field, and 5 years of experience as a data engineer, data scientist, software engineer, or related occupation.
Must possess a minimum of 2 years of experience with each of the following:
• Machine learning and deep learning;
• Physiological and mathematical modeling with statistical optimization;
• Sensor-based biomarker development on wearable devices;
• Digital signal processing, signal separation and reconstruction;
• Algorithm and software development using MATLAB and Python;
• Working with large data sources using structured (SQL) databases;
• Documentation for regulatory and FDA submission of algorithms; and
• Algorithm code development using such repositories as SVN.
*Position is open to telecommuting from anywhere in the United States. |
| Preferred Skills: |
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| Job Description: |
Sr. AI/Data Science Engineer for Medtronic, Inc. at its facility in Minneapolis, MN. Designs and develops analytics & data science algorithms that support diabetes applications to improve user experience, clinical outcomes and simplifying diabetes management. Engage in statistical and exploratory analysis of datasets such as time series data collected from medical devices (e.g. insulin pumps and glucose sensors) and smart wearable devices, alongside patient contextual data, and use the insights to build robust classification and prediction models geared toward diabetes management products using signal processing, advanced artificial intelligence, machine learning algorithms, and/or physiological modeling. Develop, optimize, and validate classification and prediction models using advanced statistical modelling, machine learning techniques (including Random Forests, AdaBoost, etc.), artificial intelligence technologies including Neural Network, CNN, LSTM (including TensorFlow, Keras, or PyTorch) and data science tools (including NumPy, Pandas, Scikit-learn, SciPy, Anaconda) in the Python ecosystem. Develop and validate physiological models by using mathematical and statistical optimization, numerical methods, and parameter estimation techniques. Develop robust and scalable algorithms for diabetes/disease management in Python and/or MATLAB. Drive novel applications of machine learning or physiological modeling to time series data from wearable devices such as glucose sensors, insulin pumps and activity trackers. Apply principles of dynamical systems to uncover characteristics and behaviors of patients from their biological signals. Evaluate algorithms against test data based on various metrics including accuracy, recall, precision, other relevant statistical metrics. able to access and work with large cloud databases. Write, maintain and peer-review pre-production level code on code repositories and versioning systems such as Git or SVN. Prepare prototypes of software and/or algorithms for deployment, including engineering reports, specifications, requirements, and summary of key results following regulatory considerations. Navigate the complexities of the medical device environment including FDA regulations and ISO 13485. *Position is open to telecommuting from anywhere in the United States.
Refer to ID 240002CD when applying |
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