Principal Data Scientist - Remote - Veradigm

Veradigm Payer 

Veradigm understands that managed care organizations, pharmacy benefit managers (PBMs), insurance companies, health plans, and other payers need to balance controlling costs with the goal of providing the highest quality of care and optimizing health outcomes for their members.

Solutions from Veradigm Payers:

• Deliver insights to drive quality outcomes cost-effectively
• Improve efficiency for themselves, their providers, and their members through high-speed clinical data exchange
• Impact point-of-care decision making positively by integrating payer guidance and prior authorization management directly in each healthcare provider's existing workflow

Position Description  

The Principal Data Scientist will lead the cultivation and expansion of an analytic culture of product development and evaluation that is best-in-class in Veradigm Payer markets. This spans the lead in designing and building explanatory, predictive, and evaluative models of health care behavior, utilization, and outcomes for the Veradigm Payer suite of solutions. This person will partner with Chief Data Scientist, executive team, and  product subject-matter-experts (SMEs) in developing business and analytic requirements that reflect methodologically sound and appropriate research designs for hypothesis testing, sampling, handling of data anomalies (e.g., outliers, missing data), mining and model building that embody current best practices and will often be suitable for publication to enhance Veradigm Payer's reputation and brand. The PDS will oversee the migration to Azure-based environment to mine, analyze, and model at massive scale and leverage this new environment to improve our analytics' scope, sensitivity, and performance. The successful candidate will demonstrate facility with complex, messy health data, knowledge of the health care sectors in which Veradigm Payer operates, mastery of the research design and appropriate statistical techniques including, but not limited to, machine learning/neural networks, classic multivariate statistics used in health and life sciences, categorical data analysis. What sets apart this role from other senior analytic roles, however, is the need to comfortably and accurately relate the business and its product requirements with the proper analytic approaches and specifics to support them. This person must be as lucid with the business needs as with the analytics to support them, and be able to lead and mentor others to institutionalize these capabilities. 

Position Responsibilities 

• Leadsand influencesteams whose members are seldom direct-reports.  
• Leads, and as needed, directly develops business cases and requirements for advanced analytics supporting new and enhanced  products. 
• Leads discovery process with stakeholders to identifyanalytic needs, important variables that might affect the desired outcomes 
• Leads or determines the methods needed to meet the business requirements, along with their execution, including (as appropriate given business requirements) 
• Research or evaluative design 
• Sampling design and data management including imputation and use of indirect or proxy measures 
• Analysis design including model contrasting, diagnostics, validation/robustness, goodness of fit, train v test, so on 
• Oversee progress to ensure adherence to the designs, resolve issues identified, advise on evaluation of outliers and missing data, results, diagnostics, and interpretation of findings and limitations.  
• Drive strategy for incorporating analytic result into normal product processing, e.g., creating scoring algorithms derived from models built, especially at data endpoints (point of care, integration with iOTdevices/apps, etc.). Ensure proper controls are in place to monitorperformance of in-line analytics from both analytic quality and machine performance. Ensure routine collection of performance data for both managerial controls and demonstrating efficacy of the analytics with their intended use. 
• Ensure analytics comply withregulatory and security requirements and with any client data-use restrictions 
• Provides on-going tracking and monitoring of performance decision systems and statistical models 
• Approve the design and deployment of enhancement and fixes to the models as needed 
• Develops and/or uses algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes 
• Performs analyses of structured and unstructured data to solve multiple and/or complex business problems utilizing advanced statistical techniques and mathematical analyses and broad knowledge of the organization and/or industry 
• Collaborates with business partners to understand their problems and goals, develop predictive modeling, statistical analysis, data reports and performance metrics 
• Develops and participates in presentations and consultations to existing and prospective constituents on analytics results and solutions 
• Interacts with internal and external peers and managers to exchange complex information related to areas of specialization 
• Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns and recommend solutions
• Use strong programming skills to explore, examine and interpret large volumes of data in various forms 

  Minimum Essential Knowledge / Skills: 

• Extensive experience in healthcare industry 
• Experience with MA, ACA and/or Medicaid Risk Scoring methodology, including familiarity with condition categories (HCC) 
• Solid knowledge of and experience with statistical techniques including parametric and non-parametric techniques, categorical data analysis, "AI" including neural networks, and other machine learning and predictive modeling techniques. Logistic regression, survival and Bayesian analytics strongly preferred.  
• Strong proficiency in statistical analysis, quantitative analysis, and predictive analytics 
• Experience interacting with large amounts of healthcare data 
• Experience working with clinical classification such as diagnoses (ICD), procedures (HCPCS, CPT) and claims processing 
• Advanced knowledge of statistical package like SAS, SPSS, or STATA  
• Strong competencywith data management language (e.g.,SQL, Databricks, Snowflake)
• Proven technical, analytical and problem solving 
• Strong written and verbal communication 
• Professional and interpersonal skills 
• Self-initiative and leadership  
• Ability to work within a team environment 
• Ability to interface with both external and internal personnel at all levels. 

Required Education / Experience: 

• Bachelor's degree in Actuarial Science, Mathematics, Statistics, or in a related field  
• 10+ years of relevant Data Scientist experience 
• 5 + years demonstrated achievement with and mastery of  quantitative and qualitative research and analytics experience 
• Solid experience supporting the development of scalable analytic and reporting s 
   

Desired Skills: 

• Strong skills and experience with Big Data, Cloud-based computing, neural networks 
• Experience using machine learning algorithms 
• Experience programming using R or Python 
•  Experience in SAS or SQL 

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