Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The AIML Evaluation org works with teams across Apple to build platforms, create methodologies, and enable partners to measure, understand, and proactively improve their products.
We are looking for an outstanding candidate to become a member of the Evaluation team to help own and drive part of our technical portfolio for Apple Intelligence. Our work ensures that Apple systems maintain the highest standards for data quality and user privacy compliance.
Description
As a Data Scientist on the AIML Evaluation team, you will play a key role in ensuring data quality and privacy compliance across some of Apple's most impactful products. You will contribute to building and maintaining monitoring systems, dashboards, and automated processes that help teams understand and uphold Apple's rigorous privacy standards.
This role blends analytical thinking with practical engineering skills in a highly collaborative environment.
Minimum Qualifications
7+ years of industry experience in Data Science, Data Engineering, or Data Analytics.
Strong programming skills in Python and SQL, with hands-on experience in data processing, analysis, and pipeline development.
Demonstrated commitment to user privacy and a working understanding of data privacy principles.
Strong collaboration and communication skills, with the ability to translate technical findings for a broad audience.
Bachelor's or Master's in a technical or quantitative field such as Statistics, Computer Science, Mathematics, or a related discipline.
Preferred Qualifications
Prior involvement in data collection design with privacy or regulatory considerations in mind.
Familiarity with data governance, compliance monitoring, or privacy-preserving data practices.
Comfort working across cross-functional teams with multiple stakeholders.
Proven ability to build or contribute to dashboards and data visualizations for both technical and non-technical audiences.
Exposure to logging frameworks or analytic instrumentation design.
