Note: The job is a remote job and is open to candidates in USA. Highmark Inc. offers a graduate internship applying data science and statistical methods to healthcare challenges. The intern will contribute to healthcare analytics projects involving data preparation, analysis, model development and evaluation, visualization, documentation, and communication of results.

Responsibilities

• Communicate effectively. This position displays effective communication skills while interacting directly with colleagues, clientele, and/or other internal or external constituencies in the planning of assignments and the resolution of day-to-day operational problems
• Under supervision, provide professional services as appropriate to the day-to-day operating objectives of the area. Receives guidance, training, and mentoring from senior personnel in planning and carrying out activities and assignments
• Undertake and/or participate in projects and programs designed to develop professional skills and expertise appropriate to the needs of the organization
• Participate in the planning and implementation of unit projects and initiatives within area of expertise and ability
• As specifically requested by management, conducts research and reporting inclusive of recommendations or alternative proposals for action
• Undertake related studies or enrichment programs as appropriate to the specific objectives of the operating unit
• Perform miscellaneous job-related duties as assigned

Skills

• Applicants must be authorized to work in the U.S. independently. At this time, we do not offer visa sponsorship for this role
• Bachelor's degree
• Pursuance of a graduate degree full or part-time in an accredited college or university
• Currently pursuing a Master's or doctoral degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field
• Experience utilizing Python for data analysis, statistical analysis, or data science applications
• Foundational knowledge of statistics, including hypothesis testing, regression, and interpretation of statistical uncertainty
• Experience with SQL and relational data concepts

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