What You’ll Be Doing
- Research, conceptualize, and implement analytical approaches and predictive modeling to evaluate scenarios, predict utilization and clinical outcomes, and recommend actions to impact results.
- Manage and execute on the entire model development process, including scope definition, hypothesis formation, data cleaning and preparation, feature selection, model implementation, validation and iteration, using multiple data sources.
- Provide guidance on necessary data and software infrastructure capabilities to deliver a scalable solution across partners and support the implementation of the team’s algorithms and models into Evolent’s product offerings.
- Contribute to the development and publication of white papers showcasing Evolent’s leadership in healthcare data science.
- Collaborate with stakeholders from clinical, operations, and product teams to identify advanced analytics opportunities to add value to Evolent’s solution offerings.
- Leverage clinical and administrative data to support other business needs related to clinical program improvement, networks optimization, and other strategic initiatives.
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.