Provider Analytics Data Scientist

Blue Cross and Blue Shield of Kansas is looking to add to our Medical Economics team and has an opportunity for a Provider Analytics Data Scientist. This position is responsible for analyzing and interpreting complex data, developing models and algorithms, and deriving actionable insights to support the business. The Data Scientist will work closely with cross-functional teams, including Provider Network Solutions, Sales, Provider Reimbursement, Health Analytics, Actuarial and Finance to understand business needs and deliver data-driven solutions. This position reports to the Manager of Provider Analytics under the Director of Medical Economics.

“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.”

Are you ready to make a difference? Choose to work for one of the most trusted companies in Kansas.

Why Join Us?

• Family Comes First: Total rewards package that promotes the idea of family first for all employees; including paid time off and family first leave.
• Professional Growth Opportunities: Advance your career with ongoing training and development programs both through our internal Blue University and external opportunities.
• Dynamic Work Environment: Collaborate with a team of passionate and driven individuals.
• Trust: Work for one of the most trusted companies in Kansas.
• Inclusive Work Environment: We pride ourselves on fostering a diverse and inclusive workplace where everyone is valued and respected.

Compensation

$105,920 - $126,000

Exempt Grade IT&S 17

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.

What you’ll do

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

What you need

• Bachelor's degree in computer science, statistics, mathematics, engineering, or a related field.
• In lieu of a degree, minimum of six years' experience as a data analyst, data scientist, or related roles.
• Minimum of three years' experience as a data analyst, data scientist, or related roles.

Knowledge/Skills/Abilities

• 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 stati