Cone Health - Data Scientist/Statistician

paid / Greensboro, NC (remote) / full-time

Cone Health, a large health system in North Carolina serving around a million residents is looking to hire a data scientist (intermediate). You'll join a team of data scientists who work primarily in R. If you have a solid background in statistics and programming, please still apply even if you lack health care experience. The majority of the team did not start in health care. See the job posting for more details.

The Data Scientist/Statistician is an experienced advanced analytics resource on the Insight Discovery & Computational Modeling team within the Cone Health Enterprise Analytics department. The Data Scientist/Statistician leverages the tools and methods of applied data science to generate business and clinical value for Cone Health through discovery of new insights/knowledge.

This opportunity is open to remote candidates as employees on this team can work off-site.

The role of the Data Scientist at Cone Health is to:

  • 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 to staff at the Data Scientist level.

  • The result of the data scientists 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.


  • Demonstrate attention to detail and initiative in discovering errors in data or analyses, or determining the need for additional, follow-up analysis arising from the original assignment.

  • Develop knowledge and expert understanding of Cone Health clinical and business initiatives to ensure value-adding design and interpretation of analysis.

  • Independently, or in teams, produce a combination of data mining, predictive modeling, simulation modeling or other quantitative analyses to provide new insights into drivers of clinical risk and financial performance.

  • Produce customer-oriented reports that provide business context for data science-based analysis and recommendations, requiring only moderate revision by the Enterprise Analytics leadership.

  • Represent Enterprise Analytics leadership as a data science expert in business engagements with mid-level leadership when called upon to do so.

  • Routinely apply data extraction and manipulation skills, complex analysis methods, statistical analysis, and data visualization tools to daily work.

  • Serve as consultant regarding advanced data mining and predictive modeling methods, as well as application of scientific research principles to knowledge discovery.



  • Required: Bachelor degree in a quantitative, analytical discipline such as data science, mathematics, statistics, operations research, actuarial science, or the physical sciences.

  • Preferred: Masters Degree in an analytical discipline.



  • Minimum of three (3) years of experience applying data science and/or other advanced analytics methods to very-large scale information sources required. Four years is preferred.

  • Demonstrated expertise in relevant data science or analytical methods, particularly as applied in the healthcare domain, may reduce time-in-position requirement.

  • Prior hands-on experience developing, applying, and interpreting results from successful (i.e., practical and impactful) analytics projects.

  • Working knowledge of data science tools and methods, including machine learning and predictive modeling.

  • Demonstrated proficiency with at least one of the following tools is required: R, Python, RapidMiner, SAS/Enterprise Miner, Statistica, AnyLogic, or BayesiaLab. Experience with similar tools will be considered.

  • The ability to design and apply multiple advanced data mining, statistical analysis, and predictive modeling methods under limited guidance from senior data scientists or the Executive Director is required.

  • Demonstrated experience working with large, complex, relational databases is required.

  • Demonstrated experience with data extraction, data manipulation, and reporting is required.

  • Demonstrated evidence of advanced problem-solving skills in the business environment.

  • Experience presenting analytically-derived findings to mid-level or 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.

  • Understanding of HIPAA and other applicable statutes or regulations concerning patient privacy and appropriate use and sharing of healthcare data is strongly preferred.

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