Blue Cross and Blue Shield of Kansas is looking for an Alternative Payment Models Data Scientist to join our Medical Economics team. This position is responsible for identifying, extracting, organizing, storing, analyzing, reporting, and modeling data to support provider reimbursement strategies and initiatives. The information will be used to identify opportunities to reduce healthcare cost and utilization through alternative payment models. The information will be used for strategic planning associated with reimbursement levels as part of provider network and contract negotiation. The Alternative Payment Models Data Scientist will work jointly with Actuarial Research, Provider Relations, Medical Affairs, Compliance, Information Technology, and outside vendor teams to identify and act on opportunities to perform analysis, update systems, and maintain core components impacting provider reimbursement.


"This position is eligible to work remotely (8 or less days a month onsite) or hybrid (9 or more days a month onsite) in accordance with our Telecommuting Policy. Applicants must reside in Kansas or Missouri or be willing to relocate as a condition of employment."



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Why Join Us?

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  Family Comes First: Total rewards package that promotes the idea of family first for all employees; including paid time off and family first leave.


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  Professional Growth Opportunities: Advance your career with ongoing training and development programs both through our internal Blue University and external opportunities.


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  Flexibility: Options to work onsite and hybrid available.


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  Make a Positive Impact: Your work will directly contribute to the health and well-being of Kansans.


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  Inclusive Work Environment: We pride ourselves on fostering a diverse and inclusive workplace where everyone is valued and respected.

• Blue Cross and Blue Shield of Kansas offers excellent competitive compensation with the goal of retaining and growing talented team members. The compensation range for this role is a good faith estimate, it is estimated based on what a successful candidate might be paid. All offers presented to candidates are carefully reviewed to ensure fair, equitable pay by offering competitive wages that align with the individual's skills, education, experience, and training. The range may vary above or below the stated amounts.

• Data Analysis & Interpretation: Analyze large and complex data sets from various sources to identify trends, patterns, and correlations. Translate data findings into actionable insights and recommendations.


• Model Development: Develop, test, and deploy predictive and prescriptive models and scenario forecasting using machine learning and statistical techniques. Continuously evaluate and improve model performance. Analyze, estimate, and report return on investment for annual changes to provider reimbursement under various alternative payment models.


• Data Visualization: Create compelling data visualizations and dashboards to communicate findings and insights to both technical and non-technical stakeholders.


• Collaborate & Communicate: Work with business stakeholders to understand their needs and translate them into data-driven solutions. Present findings and recommendations in a clear and concise manner. Support teammates by maintaining up-to-date, thorough, and clear documentation on data sources, preparation processes, mathematical models, dashboards, and other business intelligence activities.


• Data Management: Ensure data quality, integrity, and security. Develop and implement processes for data collection, cleaning, and preparation. Develop solutions to address shortcomings of data (e.g. data that is missing or incomplete).


• Research & Innovation: Stay current with the latest industry trends, tools, and technologies. Explore and implement new methodologies to enhance data analysis capabilities.

• Bachelor's degree in Computer Science, Statistics, Mathematics, Engineering, or a related field.


• Experience with and an understanding of data warehouse structures, data extraction tools, analytics software and methods, and data modeling is required. Experience with machine learning or predictive modeling is required.


• Three years' experience with technology, statistics, hospital administration, health care reimbursement, applied mathematics, financial econometrics, or another relevant field is required.


• Technical Skills: Proficiency in programming languages such as Python or R. Experience with data manipulation tools (e.g., SQL, pandas). An understanding of data warehouse structures, data extraction tools, analytics software and methods, and data modeling. Experience with big data and cloud platforms (e.g., AWS, Azure, Google Cloud). Ability to identify and make sense of rich data sources, manage large amounts of data, merge datasets, ensure consistency of datasets, graphically portray data to gain insights, build statistical models, understand data and model shortcomings, and effectively communicate findings.


• Data Visualization: Familiarity with data visualization tools (e.g., Tableau, Power BI). Demonstrated experience with creating accessible, insightful, compelling, and branded data visualizations.


• Analytical Skills: Strong analytical and problem-solving abilities. Ability to interpret complex data and provide actionable insights. Ability to apply, validate, and interpret results in a variety of machine learning contexts.


• Communication Skills: Excellent verbal, visual, and written communication skills. Ability to present complex data and insights to non-technical stakeholders effectively.


• Decision Making: Adept at identifying underlying mathematical and statistical assumptions of a given dataset or algorithm and to implement and interpret results appropriately. Ability to make decisions using independent judgment and creativity to resolve issues and overcome roadblocks.


• Collaboration: Ability to work collaboratively and build relationships with experts throughout the company in a variety of business areas. Strong interpersonal skills and a proactive attitude.

• Master's degree or higher preferred.


• Experience with value-based or alternative payment models is preferred.


• Experience with and knowledge of the healthcare delivery system, health insurance industry, and clinical data is preferred.

• Base pay is only one component of your competitive Total Rewards package:
  
  
  
  • Incentive pay program (EPIP)
  
  
  • Health/Vision/Dental insurance
  
  
  • 6 weeks paid parental leave for new mothers and fathers
  
  
  • Fertility/Adoption assistance
  
  
  • 2 weeks paid caregiver leave
  
  
  • 5% 401(k) plan matching
  
  
  • Tuition reimbursement
  
  
  • Health & fitness benefits, discounts and resources