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KDnuggets Home » Jobs :: Verisk: Analytic Scientist, Pharma ( 13:n03 )

Lead Analytic Scientist, Pharma


Join a dynamic, growing company providing important tools to control fraud, waste and abuse in health care and experience the exciting growth of Utah's "Silicon Slopes" along the Wasatch Range.



Verisk HealthCompany: Verisk Health
Location: Salt Lake City area, UT
Web: www.veriskhealth.com

VERISK HEALTH, PAYMENT ACCURACY DIVISION

An opportunity to be a part of a dynamic, growing company providing important tools to control fraud, waste and abuse in health care. Experience the exciting growth of Utah's "Silicon Slopes" along the Wasatch Range. Salt Lake City was recently ranked by respondents to a www.CareerBliss.com survey as one of the top cities to achieve career happiness. Life along the Wasatch Range offers many great benefits outside of the office as well, including a myriad of outdoor activities, a revitalized city with many and varied attractions, and a great place to raise a family.

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Responsibilities include:

  • Assist with development of new Pharma predictive modeling initiatives at the project and product level. Suggest innovative analytic methods that result in a technically superior product and/or create a competitive advantage, as well as meet design requirements and project timeline. Innovate in the development of new capabilities and business opportunities using a multi-pronged approach to fraud and abuse detection, including provider, patient, claim, and other perspectives.
  • Identify, research and recommend internal and external data sources needed for modeling. Develop specifications for structure of analytic data set and layout, and execute the plan for exploratory analysis of data.
  • Serve as lead technical resource in developing and validating fraud models, including devising novel implementations and coaching junior scientists. Develop process and metrics to monitor model performance. Review reports and make recommendations for needed model refits/enhancements. Provide pilot testing support and analyze test results if needed.
  • Develop and execute business diagnostics to enable productization and deployment.
  • Create content and serve as technical resource in development partner updates. Develop customized models for development partners. Maintain a strong working partnership with domain experts and development partners.
  • Create original publications including technical papers, white papers and byline articles. Keep abreast of business trends / product needs. Research literature to stay current on technical methods or to solve specific problems. Communicate with diverse audiences including technical stakeholders, clients, and at trade industry events.

Requirements include:

  • Support and develop junior team-members.
  • Master's degree (PhD preferred) in a quantitative field is required.
  • 8+ years' professional experience building predictive models on very large datasets required. Academic experience at the PhD level could be partially substituted for professional experience.
  • 7+ years of experience with statistical analysis and modeling software such as SAS, IBM SPSS, Statistica, or R is required. Experience with datamining platforms such as SAS EnterpriseMiner, IBM SPSS Modeler, Statistica DataMiner, or equivalent is preferred.
  • Professional experience applying predictive modeling techniques in pharmacy claims or healthcare verticals is strongly preferred.
  • Demonstrated expertise with data reduction techniques and statistical and predictive modeling methods (e.g., GLM/Regression, Trees, Neural networks, etc.) is required. Exposure to, and experience with, techniques such as Network mining, Text mining, Geo-spatial analytics, etc. is strongly preferred.
  • Strong verbal and written communication skills are required, including ability to present in public forums and conferences.
  • Demonstrated ability to manage projects to required deadlines.
  • Demonstrated ability to work with diverse business and client stakeholders.
  • Demonstrated ability to guide and mentor junior candidates.

_Contact_:
Apply online


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