At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly.
Do you bring passion and dedication to your job? If so, we are looking for someone like you.
Description
The Performance Analytics team in Paris sits at the intersection of software engineering and data science, focused on the streaming and application performance of Apple's third-party apps, primarily Apple TV and Apple Music. We act as the bridge between deep technical expertise and the broader engineering organisation, turning complex telemetry into insights that drive real product decisions.
We have built a solid data infrastructure. The next challenge is making that data work harder, surfacing the right signal, at the right time, to the right engineer. The goal is for any engineer in the org to know, without asking the performance team, whether their latest release improved or degraded performance, and what to do about it.
This role is for someone who combines strong engineering instincts with a data-driven mindset, someone who ships tools that empower others, and who proactively identifies opportunities that teammates may not even know to ask for. Many of the engineers we work with are not yet used to a data-driven approach, and a big part of this role is bringing them along.
Preferred Qualifications
Consultative mindset - able to listen deeply and proactively surface opportunities that teammates didn't know they needed.
Experience making complex data accessible to non-expert users.
Background in application or streaming performance is a strong plus.
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field. Relevant industry experience in a software engineering or data engineering role.
Minimum Qualifications
Solid foundation in data science, including statistics, A/B testing, regression detection, and performance analysis.
Comfortable with data engineering and able to work with existing pipelines as extend them where needed.
Strong software engineering skills, with a track record of shipping real tools used by others, not just analyses.
Able to build clean, usable frontend interfaces and web apps on top of existing data infrastructure.
Proficient in Python, JS/TypeScript.
