Associate Data Science Analyst (Limited Tenure)
The Associate Data Science Analyst will support senior analysts by performing descriptive analytics, data mining, and visualization on both structured and unstructured datasets. The role involves scripting, data extraction, and reporting to deliver actionable insights for business problems.
Skills required
About this role
This position 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. Other responsibilities: Provides data insights for business problems that can be approached with analytics techniques to collect, explore, and extract insights from structured and unstructured data. Has 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.
Qualifications
Note: 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.
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. Ability to develop predictive models to address various business problems through leveraging advanced statistical modeling, machine learning, or data mining techniques, is preferred. 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 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.
