AIML - Sr Data Scientist, Evaluation

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. Partner with product, engineering, and data science teams to support compliance-aware feature development — consulting on new feature design, flagging privacy considerations, and identifying monitoring requirements early in the product lifecycle. Build and maintain automated data pipelines, compliance checks, and dashboards that provide clear visibility into data quality and policy adherence over time. Investigate and triage data quality and compliance issues, help quantify their impact, and communicate findings clearly to both technical and non-technical audiences. Perform ad hoc analyses to support ongoing compliance work to inform decision-making across the team. Successful candidates will have a genuine passion for user privacy and strong communication skills. You should be comfortable operating in a cross-functional environment with some ambiguity, and be eager to grow your technical skills alongside experienced teammates. 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. 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.

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