Search Data Scientist - Maps Evaluation

Apple Maps is changing, and data is in the driver's seat. Our mission is to build the best map in the world. We work in a fast-paced data-focused environment where Data Scientists are given runway to own big projects and drive impact across the Maps organization.

Description

We are looking for a talented, detail-oriented Data Scientist to join our cross-functional team, focusing on the deep evaluation of Apple Maps search services and features. This role is critical in measuring and improving search relevance and quality by analyzing large datasets, designing evaluation strategies, and interpreting feature usage patterns. We work directly with the Engineering and Product teams responsible for search, recommendation, and other algorithms that impact our millions of users every day.

Responsibilities

• Use data intuition to translate hard product goals and business problems into solvable data science problems
• Design, create and validate actionable metrics, at both the component level and to measure overall user engagement and experience
• Work with human-labeled datasets and relevance judgments to evaluate ranking algorithms
• Conduct exploratory data analyses to mine large volume of data, extract insights, and recommend opportunities for search product improvements
• Automate analyses and pipelines via SQL and Python-based ETL frameworks
• Communicate insights to partner teams to influence product direction with data
• Build data products (feature datasets, analyses, models, etc.), dashboards and automation to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management

• MS/PhD in Computer Science, Statistics, Physics, Operations Research, or similar quantitative domain
• 3+ years experience with data analysis at web scale or relevant work experience
• Proficient in Python
• Proficient in at least one database language (e.g., SQL, Snowflake)
• Capable of translating business questions and needs into technical requirements, and using statistical techniques to find solutions
• Solid communication and presentation skills

• Prior work experience with human-labeled datasets
• Experience assessing the quality of unreleased product features
• Prior proven industry experience with large data sets using technologies like Hadoop and Spark
• Experience writing pipelines for automating analytics tasks at scale