Overview
We are looking to add a Senior Data Scientist to join our team. The ideal candidate will hold a PhD in Computer Science/Data Science with focus on biometric analysis OR have a minimum of 2-3 years of experience post-grad school OR 5-year experience post-undergrad as a Data Scientist or Machine Learning Engineer. Proficiency in Python and experience with Data Science is a must. Experience with Time Series Data / Analysis, Biometrics, Small Data Analytics, TensorFlow, Keras, analysis techniques (statistics, machine learning, signal processing, and data mining) is highly desirable. Start-up experience is a plus.
Senior Data Scientist (Biometrics) Responsibilities:
As a member of our R&D team, you will develop new algorithms based on our sensors and wearable technologies and develop and test new models using a variety of machine learning approaches. You will also study data, prototype devices, and use insight to test hypotheses for development.
- Feature discovery, building and optimizing models using machine learning techniques to generate health-sensitive metrics from the analysis of real-world data
- Collaborating with Data Science and Engineering teams in the automatization of biomarker discovery pipeline
- Collaborating with Clinical and Regulatory teams in the validation of biomarker performance and development practices
- Extending company’s data with third party sources of information when needed
- Enhancing data collection procedures to include information that is relevant for building analytic systems
- Processing, cleansing, and verifying the integrity of data used for analysis
Skill and Qualifications
- PhD in Computer Science/Data Science with focus on biometric analysis OR minimum of 2-3 years of experience post-grad school OR 5-year experience post-undergrad as a Machine Learning Engineer or Data Scientist
- Proficiency in Python
- Machine Learning experience (implementing real data to deploy and develop products
- B.S. or higher in computer science, computer engineering, or electrical engineering
- Experience with Time Series Data / Analysis
- Experience with small data analytics
- Experience with biometric data/real-world data (keystroke, voice, accelometer, face analysis, etc.)
- Analysis techniques (statistics, machine learning, signal processing, and data mining)
- Experience with Python machine learning tools, Scikit-Learn, Keras, Tensorflow
- Experience using query languages such as SQL
- Experience with NoSQL databases, such as MongoDB
- Data-oriented personality
- Great communication skills
