DATA SCIENCE INTERN
We are looking for a Data Scientist to join as a summer intern and possibly a core team member after the internship ends. We are currently based in Boston, MA in the Back Bay area. An ideal candidate would work on site at least part-time. We are looking for someone who fits with our small team and can function well with a lot of autonomy. We want the candidate to be excited about the future of health and fitness and about creating a unique hardware-software experience.
We are an early stage company developing smart clothing with integrated bio-sensors that wirelessly connect to mobile software applications. Applications include fitness and health monitoring, athletic performance assessment, and coaching.
Monitoring breathing and movement has been difficult and not user friendly in the past. Bulky camera systems and face masks are the standard. We have solved the problem by developing soft sensors integrated into garments to measure breathing, heart rate, and motion. Signal processing and biomedical analysis of sensor data will provide users with clinical-grade information about their health, fitness, and progress. Our sensors are comfortable, machine washable, and invisible. The Tyme Wear shirt pairs wirelessly with a mobile device to upload data where it can be visualized, analyzed or shared.
The ideal candidate would have experience designing, developing, and evaluating statistical, Machine Learning (ML), and Artificial Intelligence (AI) algorithms
- Design, develop, and evaluate statistical, ML and AI models on physiological data (e.g. breathing rate, heart rate, minute ventilation) and movement data (e.g. speed, cadence, power)
- Data analysis, visualization, and modeling with small and large datasets of time-series or sequential physiological and movement data
- Data cleaning and transformation for optimal ML and AI modeling
- Bachelor’s degree (or a rising college senior) in Computer Science or related field
- Strong background in mathematics and statistics
- Experience developing ML and AI algorithms for processing time-series or sequential datasets
- High proficiency in Python and specifically with data analysis and machine learning libraries (i.e. numpy, pandas, scipy, sklearn, keras, TensorFlow)
Nice to have
- Master’s candidate in Computer Science or related field
- Experience analyzing physiological signals and systems
- Recreational athlete and better yet specifically in endurance sports such as running and/or cycling.
Contact info: firstname.lastname@example.org