The Clinical Strategy and Innovation (CSI) unit is growing its Analytics and Evaluation function to address the challenges of a changing healthcare market.  As a strategic business partner, we work with teams throughout the enterprise, providing insight into consumer behavior, provider behavior, and program effectiveness through effective modeling, segmentation, targeting, and clinical program evaluation. 

The preferred candidate will have professional experience in developing sophisticated analytic capabilities, resulting in analytical insights for optimizing clinical and business opportunities.  Candidates for this position will have experience in areas such as biostatistics, predictive modeling, population-based segmentation, optimization, and business intelligence analytics.

Primary Expectations of the Position

-Leverages a thorough understanding of advanced statistical and analytical techniques to discern the primary drivers of healthcare claims costs and utilization of insured populations.

-Acts as a consultant to managers and executives across the organization by providing timely, innovative, and objective analytical insights with but not limited to business case modeling, evaluation support and outcomes effectiveness.

-Conducts complex analyses, formulates insights, and summarizes and synthesizes results for presentation to management or external stakeholders.

-Develops problem definitions and formulates hypotheses relevant to the specific business environment.

-Plans and executes evaluations of marketing and health and wellness programs which may involve a number of varied outreach channels including clinical provider-targeted or consumer marketing interventions.

 

Required Toolset

-Experience using SAS and SQL analytical development tools with large (>50k) and small datasets to execute analyses and measure and develop key metrics

-Advanced statistical programming skills are necessary to mine WellPoint claims and eligibility databases and if necessary identify areas of improvement for current processes, products, services, or analytic models

-Demonstrated skill at collecting and merging data from multiple sources and working with large, complex datasets

-Ability to conceptualize and build analytic models (e.g., risk-adjustment, trend forecasting, predictive modeling), and be expected to:

-Check accuracy of input and output data

-Interpret model diagnostics

-Measure model lift

-Effectively communicate the modeling process logic and results to stakeholders

 

Category I

-Master's degree in Biostatistics or Statistics related discipline, or MS, ABD or PhD in health services research, epidemiology, engineering, public health, operations research or social sciences with 2–4 years strong quantitative/statistical training/experience strongly preferred

-3–5 years of healthcare and/or consumer data analysis experience strongly preferred

-2+ years experience in the development of predictive models preferred

-Experience with industry standard clinical code sets, predictive modeling risk adjustment tools and episode groupers and measures, such as HEDIS, preferred

-Experience with Teradata, SQL Server, TSQL or equivalent preferred

-3–5 years direct experience manipulating and processing large multi-source datasets (>50k rows) with SAS or SQL statistical programming tools required

 

Knowledge and experience with advanced statistical concepts and data mining techniques such as:   logistic and linear regression, multilevel models, CHAID segmentation, survival analysis, Bayesian methods, parametric, non-parametric, social network analysis and time-series forecasting.

Experience communicating both verbally (teleconferencing, one-on-one, to groups) and in writing (emails, letters, reports, presentations) to various audiences (work groups, teams, company management, prospective acquisitions, external clients).

 

 

Category II

 

-Master's or Ph.D. degree in Biostatistics or Statistics related discipline, or MS, ABD or PhD in health research, epidemiology, engineering, public health, operations research or social sciences with 5–10 years strong quantitative/statistical training/experience strongly preferred

-5–10 years of healthcare and/or consumer data analysis experience strongly preferred

 

Working knowledge and proven experience with advanced statistical concepts and data mining techniques such as:   logistic and linear regression, multilevel models, CHAID segmentation, survival analysis, Bayesian methods, parametric, non-parametric, social network analysis and time-series forecasting.

 

-5+ years experience in study design and development of predictive models preferred

-Extensive experience with Teradata, SQL Server, TSQL or equivalent preferred

-5–10 years direct experience manipulating and processing large multi-source datasets (>50k rows) with SAS or SQL statistical programming tools required

-Able to assess project resource needs, lead projects and work closely with high level customers or stakeholders.