Senior Data Scientist - Machine Learning

Biofourmis is a rapidly growing, global digital health company filled with committed, passionate professionals who care about augmenting personalized care and empowering people with complex chronic conditions to live better and healthier lives. We are pioneering an entirely new category of medicine by developing clinically validated, software-based therapeutics to provide improved outcomes for patients, smarter engagement & tracking tools for clinicians, and cost-effective solutions for payers. We are collectively devoted to a single-minded idea: powering personally predictive care.

Our dynamic growth has been marked by quadrupled headcount in the last 12 months via both expansion & acquisition, yielding a global footprint with offices in Boston, Singapore, Bangalore, and Zurich. We are backed by prominent international venture capital investment & have cultivated relationships with worldwide healthcare stakeholders over the last 5 years. Our talented team features numerous PhD’s in Data Science and Biostatistics, over 80 patents, prolific scientific publications, world-class systems, developers & engineers, and leaders in the clinical operations space.

Summary:

Biofourmis is looking for smart and capable Data Scientist on our Data Science team to join our ranks. The ideal candidate should have the passion to use data from biosensors and advanced machine learning techniques for making sense of biosensor data. We are building an end-to-end service that integrates seamlessly into the lives of those patients via multiple touchpoints on front-end while providing intelligent analytics on the backend.

Responsibilities:

• Research and development of algorithms to detect abnormal subtle changes in physiology using biosensor data in real-time.
• Research and development of algorithms to derive clinical derivative parameters from continuous biosensor data including building disease specific models for patient’s health deterioration.
• Design and architect the entire workflow of the algorithms that includes data inputs, outputs and database storage.
• Optimize data analysis processes and systems for better efficiency and maintenance.
• Conduct epidemiological research to analyze the patterns, causes and effects of health and disease in the cohort of collected patient data.
• Documentation which clearly explains how algorithms have been implemented, verified and validated.

Experience / Training:

• Hands on experience with development of end-to-end data analytics solutions including data exploration/crawling, personalized machine learning model building and performance evaluation.
• Knowledge in big data technologies including cloud computing/distributed computing and data visualization.
• Background in or exposure to healthcare data, human physiology or cardiology is preferred.

Education:

• Masters or PhD in Computer Science, Electronic Engineering or related fields.
  
  

Skills:

• Proven experience to build machine learning pipeline; Understanding software architecture design is a plus.
• Familiar with clinic pathway or treatment guidelines for cardiovascular disease or oncology. Understanding the fundamentals of physiology/pathology/pharmacology is a plus.
• Proficient with time-series data analysis, anomaly detection, unsupervised learning, hypothesis testing.
• Proficient with programming in Python. Strong Programming in R or C/C++ is a plus.
• Good research ability and critical thinking skills.
• Excellent written and verbal communication skills