Data Scientist - Fraud Engineering, Algorithms, and Risk

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


Role Number:200173371
Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Internet Software and Services is responsible for delivering cutting edge applications like the App Store, iTunes, Apple Music and iCloud that are used by hundreds of millions of users every day across the globe. Our team ensures the trust and safety of Apple services through a combination of threat modeling, data analysis, and machine learning. We are seeking a data scientist with a drive to turn the huge amounts of data generated by these applications into insights that enhance safe customer experiences. A successful candidate will have a bent for self-directed research and have the ability to tell stories using data. You will work with product teams, data engineers, and experts in machine learning to measure and monitor trust and safety issues across Apple's services. We foster a collaborative work environment, but allow solution autonomy on projects.

Key Qualifications

  • Working knowledge of big data tools preferred (SQL, Spark, and Splunk)
  • Excellent interpersonal, written, and verbal communication skills
  • Confidence working independently and making key decisions on projects
  • Knowledge of machine learning algorithms including classifiers, clustering algorithms, and anomaly detection a plus


Our team is responsible for ensuring trust and safety across Apple’s Internet Software and Services organization. You will work hand-in-hand with other engineers, program managers, and business partners to understand problems, define solutions, execute plans, measure and communicate results on a regular basis.

Education & Experience

Ph.D. or Masters in a quantitative field, such as Computer Science, Applied Mathematics, or Statistics, or equivalent professional experience.

Additional Requirements