Chief Data Scientist

We are looking for a Chief Data Scientist to join our ambitious team in building the most valuable digital health company on this planet. If creating societal change is on your bucket list, you have found the perfect opportunity to do just that. 

Approximately 20% of adults suffer from chronic pain. Patients suffering from it have physical difficulties limiting their everyday life and ability to work. Chronic pain also causes depression, anxiety and stress. In other words, it has a major effect on the quality of life of those suffering from it. 

This is an enormous market and it is vastly underserved. That is why we are building the first truly personalized, science-based, and data-driven pain management solution for chronic pain patients. We are a well-funded, high performing multidisciplinary team comprising design, engineering, and business with cutting edge science from the Apkarian Lab at Northwestern University.

What you will do

You will lead the development of dynamic prediction algorithms for health outcomes. As the hub of our data science team, you will collaborate closely with a powerhouse research team at Northwestern University, led by neuro-imager and chronic pain expert Vania Apkarian. You will explore, iterate, and optimize models based on a rich and expanding proprietary clinical data set. You play an active role in defining the analytical paths we pursue. As our Data Science Leader, you will coordinate efforts between technical and data science teams based in Finland and Armenia, respectively. This is a rare opportunity to build a transformational new model of chronic pain treatment that will change the lives of hundreds of millions worldwide. 

Your Responsibilities

• Deliver AI/ML algorithms from conception to launch: Build end-to-end machine learning systems on large scale clinical data.

• Research methods and architectures, read papers, implement and deploy new algorithms.

• Establish our digital laboratory for AI/ML, together with our team in Armenia, in accordance with relevant data legislation.

• Work with latest AI/ML frameworks.

• Communicate results and explain models with R&D and commercial teams in Finland and Armenia.

 Requirements

• Trained in Computer Science & Statistics / Math, e.g. MS or PhD in Computer Science, Statistics, Data Science, Mathematics, Machine Learning, Econometrics, Biomedical Engineering, or a related field. 

• Demonstrated track record of building and using machine learning models on large clinical data sets, e.g. using deep learning.  Peer-reviewed publications considered a strong asset. 

• Demonstrated ability to design and implement novel algorithms and methods. 

• Background in scientific programming. 

• Experience with exploratory and statistical data analysis, with a zest for discovery. 

• Excellent communication skills: comfortable interfacing between academia and industry and between cross-cultural milieu.  

Assets

• Extensive expertise in Python or R.

• Natural curiosity and interest to actively monitor latest domain developments.

• Past experience in technical and medical startups.

• Entrepreneurial mindset.

What we offer you:

• Competitive salary (including possibility of equity) and health benefits.

• Professional growth opportunities.

• Remote flexibility.

• Open vacation policy.

• Gym membership.

• Collaboration with achievers and dreamers who make big things happen.

Why we think you’d like it here

We care about our employees and value proactive communication. Our interactions are based on empathy, respect, and a dry sense of humor, and we want you to be you! We strive to maintain a work environment in which you feel appreciated and safe to express yourself. Like our work, we are ambitious. We achieve our goals by keeping promises and supporting one another, as you should in a team. Our team is united by a drive to create meaningful change for people who suffer with pain, and our work will impact the lives of hundreds of millions of people.

Something Corporation does not discriminate on the basis of age, ethnicity, religion, gender, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other legally protected status.