Associate Data Science Analyst (Limited Tenure)

About the Role

This is a one year, limited tenure, hybrid position. The employee is required to live within 100 miles of the assigned Mayo Clinic campus/site. On-site expectations are determined by the supervisor and will be discussed during the interview.

Key Responsibilities

• Utilizes data analysis, data mining, pattern analysis, data visualization, reporting, and data management skills.
• Supports projects under close supervision of senior data analysts or data scientists.
• Types of work include descriptive analytics, data query scripting, data analysis, data engineering, visualizations, and forecasting.
• Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data.
• Possesses basic expertise in the data science methods used to analyze data, and knowledge of data types, topics, and scientific challenges and approaches.
• Executes analytical procedures in the framework of a specific project work request.
• Modifies scripts or software applications to support data management, data extraction and data analysis as required.
• Contributes to the interpretation of data analysis and to writing reports.
• May help customers understand the data set and provide training and suggestions for improvement on the data request.
• Leverages communication and interpersonal skills and works with subject matter experts.
• Presents findings in easy to understand terms for the business or clinical practice.

Requirements & Tech Stack

• Demonstrated application of several problem-solving methodologies, planning techniques, continuous improvement methods, and analytical tools and methodologies (e.g. machine learning, statistical packages, modeling, etc.) is required.
• Incumbent must stay current on healthcare trends and enterprise changes.
• Interpersonal skills and time management skills are required.
• Requires strong analytical skills and a commitment to customer service.

Qualifications

• Bachelor's degree in a domain-relevant field such as engineering, mathematics, computer science, statistics, physics, data science, health science, or another analytical/quantitative field.

Preferred Qualifications

• Ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques, is preferred.
• Experience writing SQL queries and developing data analysis workflows using Python (including libraries such as pandas, NumPy, or scikit-learn).
• Familiarity with cloud computing platforms, preferably Google Cloud Platform (GCP), through coursework, internships, research, or personal projects.
• Familiarity with relational databases, data modeling, and data quality concepts.
• Experience working with electronic health record (EHR), clinical research, claims, or other healthcare data is preferred.
• Experience collaborating on team-based software or analytics projects using Git or similar version control systems.
• Strong written and verbal communication skills with the ability to explain technical concepts to non-technical audiences.
• Demonstrated curiosity, continuous learning, and the ability to independently learn new technologies and analytical methods.