Data Scientist, Apple Pay

Austin, Texas, United States
Software and Services


Role Number:200203542
Join the team that provides software security technologies to help users protect their accounts. We believe in transforming your smartphone into a device that secures your digital life without sacrificing your privacy. We are seeking a data scientist that will develop solutions to bring order to unstructured data using modeling techniques. A successful candidate will have a bent for applied research with expertise in pattern mining, anomaly detection, predictive modeling, classification and optimization. The candidate will take end-to-end responsibility for translating customer needs into analytical solutions from feature engineering, implementation, model training and reporting. The role requires working in a fast paced environment, handling multiple assignments and being self driven. Candidates also need to show initiative and be able to take ownership of a problem area.

Key Qualifications

  • Strong working knowledge of data mining algorithms including classifiers, clustering algorithms and anomaly detection techniques
  • Familiarity with database modeling and data warehousing principles and SQL
  • Familiarity with Big Data tools like Spark, Hive etc.
  • Strong programming skills in Java, Python, Scala or similar language
  • Passion for problem-solving and analysis
  • Highly motivated and organized, with the ability to accept ambiguity and deliver exceptional results on tight schedules
  • Understanding of privacy-preserving techniques is a plus


Apple is looking for a data scientist to work on our software security technologies to develop and launch new products. You will work hand-in-hand with security engineers, software engineers, program managers and business partners to understand problems, define data-driven solutions, execute plans and communicate results on a regular basis.

Education & Experience

MS or PhD in quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent industry experience

Additional Requirements