About the position
Seamless user experiences are key to Meta's mission of bringing the world closer together. As a Product Analyst supporting the Quality Assurance (QA) team in the Product Quality & Experience (PQX) organization, you will partner with QA teams and platform engineers to empower Meta to deliver great product experiences at scale for people and businesses. By applying your technical skills, analytical mindset, and business intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will use data and analysis to identify and solve QA's biggest challenges. You will influence strategy and investment decisions with data, be focused on impact, and collaborate with other teams. You won't simply present data, but tell data-driven stories. This role will focus on optimizing QA operations and processes to ensure efficient, scalable, and timely functional correctness signal to ensure our products are working as designed. There will also be collaboration with our International Testing team that focuses on in-market functional correctness and usability signal.
Responsibilities
- Partner with QA teams and platform engineers to deliver great product experiences.
- Use data and analysis to identify and solve QA's biggest challenges.
- Influence strategy and investment decisions with data.
- Optimize QA operations and processes for efficiency and scalability.
- Collaborate with the International Testing team on functional correctness and usability.
Requirements
- Currently has, or is in the process of obtaining a Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- 3+ years of work experience in analytics or data engineering, or 2+ years of experience with a Master's Degree.
- Analytics experience is non-negotiable.
- Experience with data querying languages (e.g. SQL).
- Experience with scripting languages (e.g. Python).
- Basic statistics knowledge.
- Experience with operations research, forecasting, automated testing, or dev ops.
