Data Scientist - Maps Evaluation

Santa Clara Valley (Cupertino), California, United States
Software and Services

Summary

Posted: Aug 2, 2019
Weekly Hours: 40
Role Number: 200085484
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 dynamic, high impact, self-driven environment where data scientists are given runway to own big projects and drive impact across the Maps organization. We are focusing on the evaluation of Maps services and features. Our group works directly with the engineering teams responsible for search, routing, recommendation and other algorithms, and tackles many types of problems, including design of experiments, AB testing, exploratory data analysis, machine learning and data mining.

Key Qualifications

  • You are well versed in data analysis and visualization.
  • You have background in statistical programming (e.g. R, Python) and database languages (e.g., SQL).
  • You're able to work independently, as well as collaborate with others.
  • You have the ability to translate hard product goals and business problems into data science problems, draw conclusions from data, and recommend actions.
  • You can automate analytic tasks.
  • You have excellent written and verbal presentation skills.
  • Preferred Qualifications :
  • 5+ years working experience delivering and scaling highly successful and innovative experiments and data science products
  • Experience with AB testing.
  • Experience with large data sets using technologies like Hadoop, Hive, and Spark.
  • Versed in using Scala/Java.
  • Background with information retrieval and/or the mapping/transportation industry.
  • Exposure to large scale machine learning algorithms.
  • Experience with human judgement platforms (e.g. MTurk).

Description

You will build products(data sets, analysis, models, etc.) and tools to drive hypothesis generation and decision-making in partnership with engineering and product management teams. Craft actionable metrics and design effective experiments. Develop models/analysis to mine large volume of data, extract insights and explore opportunities for improvements. Automate analysis and pipelines via SQL and Python/Scala based ETL frameworks. Communicate insights to engineering, product management and executive teams, and drive product decisions with data.

Education & Experience

MS or PhD in Statistics, Computer Science, Physics, Operations Research, or similar quantitative domain. Alternatively, a comparable industry career with significant experience in data analytics.

Additional Requirements