Healthcare Data Scientist I & II
Responsibilities & Requirements
Cambia Health Solutions is working to create a seamless and frictionless health care experience for consumers nationwide. This presents a unique challenge and opportunity for innovative and disruptive solutions from the Data Office.
Our Data Scientists design, develop, and implement data-driven solutions using machine learning technologies and advanced statistical analyses. You should be passionate about finding insights in data, comfortable withlarge and fragmented data sets, and command a variety of analytic tools at your disposal.
In addition to quantitative mastery, the ideal candidate will effectively interpret and communicate strategic results to varied audiences, and provide analytic support for companywide process and operational improvement efforts. The ideal candidate is an independent, solution-oriented thinker witha strong background processing large data sets, applying analytical rigor and statistical methods, and driving toward actionable insights and novel solutions.
At Cambia, our values are fundamental to achieving our Cause of transforming the health care industry. They guide our actions and bring diverse perspectives together to improve the health care journey better for those we serve. All eight values are equally important and linked to the others: Empathy, Hope, Courage, Trust, Commitment, Innovation, Collaboration and Accountability. These values are not just words on paper - we live them every day.
- BA/BS degree (or equivalent experience) in a strongly quantitative field such as: Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, Econometrics, Biostatistics, or Public Health and 3 years of related work experience or equivalent combination of education and experience. Master's or PhD degree preferred.
- Whole-brain thinking: Possessing the ability to think creatively and demonstrate analytical skills, analyzing complex situations both alone and as part of a team, learning quickly and synthesizing solutions, options and action plans.
- Knowledge of healthcare domain, preferably with some payer experience, is strongly desired.
- Passion for improving the health care experience through data science techniques.
- Familiarity with applied data science techniques, hands-on experience with the skills below:
- Understanding of advanced analytics (e.g., statistical inference, simulation, optimization) and methods such as time series analysis, longitudinal studies, and life event modeling.
- Demonstrable knowledge of, and practical experience applying, data mining methodologies, natural language processing, and machine learning algorithms (e.g. regression, clustering, neural networks, kernel methods, dimensionality reduction, ensemble methods, decision tree models). Critical is experience in applying these techniques to real-world healthcare data and the ability to determine what to use and why.
- Experience with common languages for data science, statistics, analysis, and scripting (e.g., Python, R, SAS, MATLAB, or Scala).
- Experience with cleaning, aggregating, and pre-processing data from varied sources. Experience creating complex SQL queries for standard as well as ad hoc data mining purposes.
- Demonstrated ability to analyze and interpret qualitative data (research, feedback) and incorporate such insights into quantitative analyses.
- Practical ability to visualize data and analytical results, and excellent communication skills to effectively collaborate and communicate with a broad array of internal and external contacts.
- Strong facilitation skills, including the ability to resolve issues and build consensus among groups of diverse stakeholders.
- Demonstrated ability to work with minimal direction, with the ability to coordinate complex activities.
- Excellent oral and written communication skills to effectively interface and communicate with a broad array of internal and external contacts including leadership.
- Coursework or practical experience with machine learning, data mining, and constructing analytical models and algorithms.
- Coursework or practical experience with population health, biostatistics, demographic analysis, andprogram evaluation.
Healthcare Data Scientist I would have a bachelor's degree in Mathematics, Engineering, or Statistics and 3years of related work experience or equivalent combination of education and experience. Master's or PhDdegree preferred.
Healthcare Data Scientist II would have a bachelor's or Master's degree in a strongly quantitative field such as: Statistics, Applied Mathematics, Physics, Operations Research, Computer Science, or Econometrics, and 6 yearsof related work experience or equivalent combination of education and experience. Master's or PhD degreepreferred.