Data Management Analyst I

EXPIRED

Classification Title:

Data Management Analyst I

Job Description:

Contribute to data availability for AI-Powered Athletics project by managing the data input from wearable devices into the current Athlete Management System (AMS)

Classification Title:

Data Management Analyst I

Job Description:

Contribute to data availability for AI-Powered Athletics project by managing the data input from wearable devices into the current Athlete Management System (AMS)

Liaise with UF athletic teams to ensure equipment is functional and provide technological support where necessary.

Provide operational assistance to UF athletic teams and the UAA Sports Health and Performance Department to ensure availability and operational functionality of wearable devices.

Collaborate with AI-Powered Athletics team to develop a best practice for data collection and curation to ensure that data is useable for the project and provides accurate insights.

Increase visibility of AI-Powered Athletics project within the UF athletic teams and UAA by attending practices, games, or other athletics events, as necessary.

Manage student athlete accounts within the AMS at the beginning of the seasons to ensure that data is synchronized between wearable devices and AMS.

Analyze data from the wearable devices on the AMS platform to deliver reports and dashboards to contribute to research questions for the AI-Powered Athletics project and deliverables to the UAA Sports Health and Performance Department

Use the ‘builder’ functions on the AMS to create automations for report and dashboard generation to guide research questions for the AI-Powered Athletics project and for athlete monitoring within the UF athletic teams.

Liaise with the Research Assistant Scientist and the Director of Sports Performance and Analytics to derive actionable insights and generation of research questions from the data.

Work within the AI-Powered Athletics team to meet short and long-term research goals by understanding and leveraging the data within the AMS to derive impactful research questions.

Assist the Research Assistant Scientist on the AI-Powered Athletics project to curate and clean data from wearable sensors within the AMS.

Use technology including the AMS, Excel or a coding language to monitor the data within the AMS to ensure data cleanliness. This will include working with the Research Assistant Scientist to derive guidelines and procedures for data standards and cleanliness.

Continually monitor data from the AMS to ensure that any anomalies are flagged.

Train and oversee Sports Performance and Analytics intern students to use the wearable devices.

Create guidelines and documentation to train students to use the wearable devices to support UF athletic teams on a day-to-day basis.

Ensure continuity between academic terms and cohorts in the provision of support to the UF athletic teams

Expected Salary:

$60,000-$65,000; commensurate with qualifications and experience

Minimum Requirements:

Bachelor's degree in an appropriate area.

Preferred Qualifications:

Minimum of 3 years of previous experience with Division I intercollegiate or professional athletics program and sports science experience.

Advanced and proficient experience conducting a GPS and Athlete Monitoring System.

Ability to work with and communicate complex data to Biomechanists, Research Scientists, Data Analysts, Athletic Trainers, Strength and Conditioning Coaches, Dieticians, Physical Therapists, and Sport Coaches.

The capacity to engage effectively with others of diverse cultures or backgrounds, and strong personalities.

The ability to work a non-standard work schedule that may include evenings, weekends, and holidays.

The ability to work outside and in various weather conditions.

Special Instructions to Applicants:

In order to be considered for this position, applicants must upload a cover letter and resume with application.

This is a time-limited position.

Application must be submitted by 11:55 p.m. (ET) of the posting end date.

Health Assessment Required:

No