TaskUs

WFM - Supervisor (RTM)

Novi, Michigan, USA

Sponsorship not specified$50k-$74kDetected 6 days ago

LeadershipCommunicationProblem SolvingCritical Thinking

About the role

We are seeking an analytical and decisive leader to step into the role of WFM RTA Supervisor.
You will report directly to the WFM RTA Manager and help execute the overarching workforce strategy.
Serve as the primary on-site liaison between the Client, internal Operations teams, and the remote RTA team to ensure strict alignment on daily business goals and service level agreements (SLAs).

On-Ground Liaison & Operational Support
Support the RAD/ERT Support operations from a resource and staffing perspective, ensuring all real-time delivery expectations are met during critical incidents.
Because this role supports dynamic, high-stakes environments, we are specifically looking for professionals with a background in Autonomous Vehicle (AV) Operations or Emergency Response.

1-3 years of experience in a supervisory or lead capacity, such as an Operations Team Lead, Dispatch Lead, or Senior RTA.
Strong proficiency in Google Sheets/Excel.
Ability to read operational data and translate it into clear, immediate actions.
Exceptional verbal and written communication skills, with the ability to communicate urgency calmly and effectively to cross-functional teams.
High-level critical thinking skills with the ability to remain calm and make rapid, data-backed decisions in a high-pressure, incident-driven environment.
Leadership Background: 1-3 years of experience in a supervisory or lead capacity, such as an Operations Team Lead, Dispatch Lead, or Senior RTA.
Analytical Prowess: Strong proficiency in Google Sheets/Excel.
Communication: Exceptional verbal and written communication skills, with the ability to communicate urgency calmly and effectively to cross-functional teams.
Problem Solving: High-level critical thinking skills with the ability to remain calm and make rapid, data-backed decisions in a high-pressure, incident-driven environment.

Direct experience in Autonomous Vehicle (AV) Operations, Dispatch, or Emergency Response environments is highly preferred.
Industry Experience: Direct experience in Autonomous Vehicle (AV) Operations, Dispatch, or Emergency Response environments is highly preferred.

The People First culture at TaskUs has enabled the company to expand its workforce to approximately 60,000 employees globally.

$50,000.00 - $74,000.00 per year. Pay Transparency Statement:
The base salary range represents the low and high end of the anticipated salary range for this position across our US locations.
The "pay scale" provided is a good faith estimate of the range the employer reasonably expects to pay for the position at the time of hire.
Actual salary will be determined based on various factors including, but not limited to, the candidate's qualifications, experience, skills, and specific geographic location.

At TaskUs, we prioritize our employees' well-being by offering competitive industry salaries and comprehensive benefits packages.
Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity.
We offer a comprehensive benefits package including medical, dental, and vision insurance
and paid time off including vacation, sick leave, and holidays.

If you need reasonable accommodations in any part of the hiring process, please let us know.

TaskUs is proud to be an equal opportunity workplace and is an affirmative action employer. We celebrate and support diversity
we are committed to creating an inclusive environment for all employees. TaskUs people first culture thrives on it for the benefit of our employees, our clients, our services, and our community.
We invite you to explore all TaskUs career opportunities and apply through the provided URL https://www.taskus.com/careers/.
We celebrate and support diversity; we are committed to creating an inclusive environment for all employees.

This listing is sourced directly from TaskUs's careers page and normalized into a canonical job model.