Description
The Data Scientist 2 uses mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions. The Data Scientist 2 work assignments are varied and frequently require interpretation and independent determination of the appropriate courses of action.
Responsibilities
The Data Scientist 2 will be responsible for leveraging advanced analytics and machine learning to advance strategy and initiatives at HPS and Humana Pharmacy.
Manage and manipulate large data sets to support analytics projects
Work with business partners to identify areas of opportunity and deliver business insights
Present findings to business/technical partners; be able to present technical findings clearly to non-technical audiences
Identify and measure project outcomes
Use supervised and unsupervised machine learning to develop models that help solve business problems
Work with a diverse array of business partners and assist in requirements definition, project scoping, timeline management, and results documentation to ensure professional relationship management
Required Qualifications
Master's Degree in Statistics, Computer Science, Mathematics, Quantitative Social Sciences or other quantitative discipline
Experience in Python, R, SAS, SQL or other statistical programming language
Experience in manipulating and working with structured and/or unstructured data sets for analysis and reporting
Experience in creating reports, projections, models, and presentations to support business
Experience in using mathematics, statistics, modeling, business analysis, and technology to transform high volumes of complex data into advanced analytic solutions
Possesses an understanding of department, segment, and organizational strategy and operating objectives, including their linkages to related areas
Capable of making decisions regarding own work methods, occasionally in ambiguous situations
Must be passionate about contributing to an organization focused on continuously improving consumer experiences
Preferred Qualifications
PhD in Statistics, Computer Science, Mathematics, Quantitative Social Sciences or other quantitative discipline
Experience with pharmacy and/or health care data
Experience with Azure cloud storage and analytics solutions
Experience with Databricks and/or PySpark
Scheduled Weekly Hours
40