Apply Machine Learning and Statistics techniques to large health data sets to build new products and methodologies
Collaborate closely with a team of Data Scientists, Product, and Engineers to improve and implement methods and features
Rapidly build prototype product solutions, communicate findings, iterate
Use technologies like AWS, Spark, Python, R, SQL, and Git in addition to proprietary data mining software on a daily basis
What Youve Done
Degree in a relevant technical field (Machine Learning, Computer Science, Operations Research, etc)
5+ Years of hands-on data science experience
Highly proficient in Python and SQL
Experience with source control workflows like GitHub
Experience working with Big Data Technologies like Spark and AWS
Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
Nice to Have
Advanced degree (MSc, PhD preferred) in a relevant technical field (machine learning, computer science, operations research, etc)
Practical experience applying Causal Inferences methodologies
Experience with R preferred
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