Data Scientist (With Engineering Focus), Maps Metrics

Apple Inc. Cupertino , CA 95014

Posted 2 months ago

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. We are looking for a talented, experienced Data Scientist to join our cross-functional team, focusing on the deep evaluation of Maps services and features. We work directly with teams responsible for search, routing, recommendation, and other algorithms that impact our millions of users every day. Our day-to-day work crosses many functional areas, including experiment design, AB testing, exploratory data analysis, generative analytics, data mining, and more.

Advanced degrees in Computer Science, Statistics, Physics, Operations Research, or similar quantitative domain; (will consider MS with significant related experience). Experience with at least one programming/scripting language (e.g., Python, Scala, Java). Experience with at least one database language (e.g., SQL). Solid communication and presentation skills. Prior industry experience with technologies like Hadoop, Hive, and Spark.

Automate analyses and pipelines via SQL and Python/Scala-based ETL frameworks to help other Data Scientists generate insights faster. You will build tools (typically in Python or Scala) to drive hypothesis generation and support collaborative decision-making with our partner teams in engineering and product management.

As the domain expert of Data Science Engineering, you'll help setting up proper engineering process. Designing engineering solutions that streamline the "communications" between internal tools, and solutions that detect data logging or metrics computation issues. Communicate insights to partner teams to influence product direction with data. Utilize data intuition to translate hard product goals and business problems into solvable data science problems.

Advanced degrees in Computer Science, Statistics, Physics, Operations Research, or similar quantitative domain; (will consider MS with significant related experience).



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