Workforce Analyst

About Uber

We’re changing the way people think about transportation. Not that long ago we were just an app to request premium black cars in a few metropolitan areas. Now we’re a part of the logistical fabric of more than 600 cities around the world. Whether it’s a ride, a sandwich, or a package, we use technology to give people what they want, when they want it.

For the people who drive with Uber, our app represents a flexible new way to earn money. For cities, we help strengthen local economies, improve access to transportation, and make streets safer.

And that’s just what we’re doing today. We’re thinking about the future, too. With teams working on autonomous trucking and self-driving cars, we’re in for the long haul. We’re reimagining how people and things move from one place to the next.

Job Description

We're looking for a Workforce Analyst to develop and lead various scheduling, headcount projections and staffing efforts within our Lisbon Center of Excellence (COE). Uber COEs are contact management centers with hundreds of employees dedicated to providing world-class customer support to riders and drivers.
Uber relies on the COEs to provide support for our community's toughest issues types, handle escalations from our tens of thousands of business processing outsourcing (BPO) agents, and provide an environment to pilot support for new products or test new support modalities or processes. Accurately projecting Customer Service Representative (CSRs) staffing needs to meet response time targets is a critical enabler to delivering an extraordinary support experience. The Workforce Analyst is focused on turning data into value-driving business insights that will facilitate our ability to scale and optimize our global support network.

What you'll do

Create, analyze and monitor staffing needs for the COE (>100 employees and still growing) to optimize network resource planning
Forecast future staffing needs based on historical data and predictive analytics in order to properly staff for production, taking into account seasonality and external factors, as well as internal factors such as new product incubation, city expansions, etc. Drive continuous improvements to these Workforce Management processes in order to more accurately predict staffing needs
Present recommendations for long-term forecasts (staffing, hiring) to Senior Leadership; deliver weekly and monthly analyses to Senior Leadership on network performance and future outlook
Set realistic Service Level Agreements and create Contact Backlog reports which are distributed to multiple stakeholders; continually serve as a point of contact for a 'health check' for the business
Work cross functionally within the COE, as well as throughout the EMEA region (Regional WFM, Strategy & Planning) to be the voice of the COE and garner support in regards to team and headcount planning
Develop, manage and adhere to a financial budget in conjunction with Strategy & Planning regarding staffing levels within COE
Generate weekly work schedules for the different teams in the COE


What you'll need

Work experience in Business Analytics, Workforce Planning, Management, or Predictive Modeling is a plus
Ability to synthesize large sets of data into meaningful decisions, and make conscious business decisions off of that data
Extraordinary written and verbal communication skills
Collaborator within your team, as well as externally; you are a big thinker and never view problems that arise as microscopic, but rather take a step back to make decisions that are in the best interest of the COE, Uber, and our community
You are a resourceful self-starter, always willing to take initiative and address something hands-on, you persevere when others give up.
Optimistic leadership: you are passionate about making magic for our Community. You realize the vital role that staffing plays in appropriately cultivating positive experiences with our riders and driver partners, allowing for positive support experiences every time, all the time
Experience with Excel and preferably SQL, plenty of experience working with data.