Senior Data Scientist 

PhysIQ is a transformational leader in applying highly sophisticated technology to solve some of the most pressing problems in healthcare. More specifically, we are forging the frontier of healthcare delivery at the intersection of mobile technology and artificial intelligence. Our team is comprised of veteran technologists and world-class data scientists and our solutions set the market standard for scalability and sophistication. Furthermore, we are implementers with a proven track record of transforming an audacious technological vision into mission-critical solutions for our customers.

• Our core values are simple and are defined by integrity, passion and relentless drive toward solving the impossible.
• We are a team in its purest definition. We all pull on the rope together, in the same direction, with the same intensity.
• Our customers and their patients depend on us to deliver technology that will forever change healthcare. We are literally keeping people out of the hospital. We are changing lives.

In our world, amazing things only happen when people make them happen. If you want to make things happen and do it with a world-class of team of visionaries and doers, we encourage you to apply.

We seek a seasoned researcher at the crossroads of medicine, physiology, data science and sensors, with experience in machine learning and artificial intelligence. With physIQ, you will work with large, rare troves of millions of hours of warehoused sensor data with clinical context, an advanced library of physiology feature algorithms, and a state-of-the-art platform for collecting new data in studies you may design.

In this role, you will work with raw sensor waveforms and derived vital sign features from patients and human subjects using continuous wearable sensors in unconstrained activities of daily living, to develop and validate emergent analytics characterizing physiological health and behavior. This will rely heavily on the latest techniques in machine learning and artificial intelligence, including deep neural net and similar architectures. Our high-level objective is to harvest as much clinically useful information as is possible about patients using continuous wearable sensors, to achieve highly accurate algorithms using cutting edge data science techniques that pass muster with medical regulatory agencies. Strong validation practices are requisite.

• A successful candidate will be capable of working independently to solve the algorithmic needs of the company without hand-holding, while also being a good collaborator with other members of the Research team and colleagues in the company.

• A successful candidate will have strong organized coding skills.

• A successful candidate will have strong written communication skills and good experimental documentation practices.

Responsibilities: 

• Design, develop and validate analytical algorithms 

• Curate source data and investigate clinical cases 

• Write design and validation documentation under quality systems practices 

• Prepare publications and related market-facing validation collateral 

• Troubleshooting of production-released algorithms 

• Mentor junior staff and communicate concepts to non-research colleagues 

• Design and analyze clinical trials 

Requisite Skills: 

• 4-year undergraduate technical degree (science, engineering) 

• 4 years of post-undergrad experience with machine learning or AI 

• 2 years of post-undergrad experience with wearable sensor data 

• Expert coding skills in one of Python, MATLAB or arguably similar ML/AI dev environment 

• Proven record of working independently to deliver results

• Demonstrable knowledge of human physiology or medical data science applications 

Nice to Have: 

• Master’s degree or PhD in scientific or technical area 

• Advanced knowledge of human physiology

• Expertise in wearable sensors 

• Experience using git / gitlab 

• Experience using advanced features of Google Cloud Platform or Amazon Web Services 

• Expertise in signal processing

• Expertise in statistics

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