Key Qualifications:
Expertise in at least one area of machine learning, artificial intelligence, or statistics (e.g., health, time series, causal inference, probabilistic modeling, reinforcement learning, optimization, NLP)
Strong interest in applying machine learning methods to health-related problems and data
Ability to distill vague product experiences into concrete problem definitions
A passion for making methods robust and scalable
Skilled in explaining and presenting analyses and machine learning concepts to a broad technical audience
Experience using Python, R, C/C++, or other programming languages for machine learning
Description:
-Researching, developing and implementing the most innovative machine learning, artificial intelligence, statistics, computer vision, and NLP techniques applied to unique health data and problems
-Actively engaging with the academic community by publishing papers and presenting your work
-Transferring machine learning solutions to data scientists and engineers on product teams
-Providing technical guidance to product teams on the machine learning approaches appropriate for a task
Education & Experience
Ph.D. in Computer Science, Machine Learning, AI, Statistics, Mathematics, or related quantitative field with a strong research track record
Additional Requirements
* 10 + years of research experience in academia or industry
* Proven track record of innovation in creating novel machine learning algorithms and advancing the state of the art, especially in the health domain
* Proficiency in training large-scale models using modern machine learning packages (e.g. TensorFlow, PyTorch, autographed), and experience with data analysis stacks (such as NumPy, scipy, pandas, etc.)
* Strong fundamentals in problem-solving, algorithm design, and model building
* Passion for creating new technologies with high product impact
* Excellent verbal and written communication and presentation skills
