The Experience You’ll Need (Required):
Master’s Degree with a quantitative focus (e.g. data science program, software engineering, statistics, mathematics, computer science, health services research).
3-6 years of professional experience in an analytical field related to health service analytics, predictive modeling in health care, or other health care-related experience.
Strong technical abilities with advanced data and analytics tools and programming languages, including Python or R, and at least one database language such as SQL or Mongodb.
Foundational understanding of core concepts in applying machine learning algorithms: data cleaning, feature selection, and parameter tuning.
Strong communication skills, including both communicating with other stakeholders to fully evaluate project requirements and context, as well as communicating project results, findings, and applicability.
Ability to work independently with little technical guidance day-to-day, in a fast-paced environment.
Finishing Touches (Preferred):
Experience in SAS, SAS/CONNECT, and disparate programming language integration techniques
Proficiency in most areas of mathematical analysis methods, statistical analyses, predictive modeling, and/or machine learning (such as neural networks, random forests, gradient boosting, etc), and in-depth specialization in some areas.
Working knowledge of analyzing administrative medical claims, pharmacy claims, and/or EMR data and clinical data.
Proficiency with git or other version-control software, especially in collaboration with others.
Proficiency working at the command line / shell.
Experience in reporting and visualization tools such as R’sggplot, Python’s bokeh, Tableau, MSTR, or geo-mapping tools.
Experience building and/or using APIs.