Compensation Analyst, Animation
It's an exciting time to join the Compensation Team at Netflix as we continue to expand! We have a unique approach to compensation here which helps us attract and retain stunning colleagues around the world. Our approach to compensation is being refined for the Animation population. To help in this effort and continue to grow our animation business effectively, we need a compensation team that can work without conventional compensation structures and enable our partners to determine the right number for each individual using data, insights and resources. This requires a skill set that can balance both the art and science of compensation design.
To support what has been outlined above, we are hiring a Compensation Analyst focused exclusively on the Animation population. This person will be responsible for partnering with the internal Compensation team as well as Animation HRBPs, Talent Advisors and business leaders to consult on all things related to compensation. The Animation population consists of a significant union population, so this individual will be responsible for interpreting and maintaining the compensation elements of the applicable union agreement.
In this role you will:
- Support Compensation Partners in daily activities including providing market data to MIA, TA, and HRBP colleagues
- Support build out of compensation program for the Animation group
- Develop/run analysis identifying market movement trends, assess gaps in our market data and provide recommendations on how to close candidates
- Work with our data science and HRIS teams to build metrics and dashboards for HR and manager use
- Participate in compensation surveys
- Analyze and interpret the compensation elements of the various union agreements
- Maintain applicable union pay scale table and titling schemes
What we are looking for:
- Experience in the Animation space with a unionized population
- Strong analytical skills
- Comfortable assessing large data sets through google sheets or excel models
- Eager to learn
- Passion for compensation
- Navigate ambiguity and be comfortable with some level of inconsistency
- Experience with custom compensation programs and models