Cone Health, SW-Enter Analytics - Consulting SvcsCITY:
Greensboro, NCJOB DETAILS:
Exempt: Yes | FTE: 1.0 (40 hours/week) | Schedule: Monday-Friday, 9:00 AM - 5:00 PM | On Call: NoJOB SUMMARY:
The Data Scientist - Senior is an experienced data science resource on the Insight Discovery & Computational Modeling team within the Cone Health Enterprise Analytics department. The Data Scientist - Senior leverages advanced knowledge of the tools and methods of applied data science to generate business and clinical value for Cone Health through discovery of new insights/knowledge. The role of the Data Scientist - Senior at Cone Health is to independently:
• Apply machine learning-based data mining methods to discover new patterns in claims and care delivery data for the purpose of understanding performance of the Cone Health enterprise and/or the populations that it serves,
• Create predictive models for clinical and financial outcomes and/or population behaviors, and/or
• Build simulation models to assess the range of possible outcomes for strategic and tactical proposals, and to gain an understanding of the sensitivity to associated business levers, prior to implementation.
• Provide data science tools and methods mentorship and project leadership to staff at the Data Scientist and Data Scientist - Intermediate levels.
The result of the data scientist's work is a body of high-impact models that can be implemented in a production setting to improve member health outcomes, to increase the efficiency of care delivery operations, and to contain health care costs through health improvement and risk mitigation.EDUCATION:
Request: Master's degree in a quantitative, analytical discipline such as data science, mathematics, statistics, operations research, actuarial science, or the physical sciences.EXPERIENCE:
• Minimum of five (5) years of experience applying data science and other advanced analytics methods to very-large scale information sources required. Six years is preferred.
• Demonstrated expertise in data science and analytical methods, particularly as applied in the healthcare domain, may reduce time-in-position and/or educational requirement.
• Extensive experience developing, applying, and interpreting results from successful (i.e., practical and impactful) analytics projects.
• Advanced knowledge of data science tools and methods, including machine learning and predictive modeling or simulation modeling.
• Demonstrated expertise with multiple data science tools is required, e.g.: R, Python, RapidMiner, SAS/Enterprise Miner, Statistica, AnyLogic, or BayesiaLab. Experience with similar tools will be considered.
• Extensive experience designing and applying multiple advanced data mining, statistical analysis, and predictive modeling methods independently is required.
• Demonstrated experience working with large, complex, relational databases is required.
• Demonstrated experience with data extraction, data manipulation, and reporting is required.
• Demonstrated expertise applying advanced problem-solving skills in the business environment.
• Experience presenting analytically-derived findings to senior leadership is required.
• Analytics experience in the healthcare delivery or health insurance industries is strongly preferred. Relevant experience in other industries (e.g., retail, social media, financial services) will be considered.
• Two-or-more years of experience applying advanced analytics tools and methods to healthcare data is strongly preferred.
• Two-or-more years of experience in a healthcare operations environment (health system or insurer) is strongly preferred.
• Prior supervision of individual, or teams of, data scientists is strongly preferred.
• Understanding of HIPAA and other applicable
statutes or regulations concerning patient privacy and appropriate use and sharing of healthcare data is strongly preferred.LICENSURE/CERTIFICATION/REGISTRY/LISTING:
Valid Driver's License | Valid Driver's License
Cone Health is an equal opportunity employer. If you require assistance with our online job submission process, please contact our team at 866-266-3767 to request an accommodation.