Senior Data Scientist, Machine Learning Platform TechnologiesApple • Cupertino, California, United States
Senior Data Scientist, Machine Learning Platform Technologies
Apple
- Cupertino, California, United States
- Cupertino, California, United States
Über
You will design product health metrics and ensure measurement is built into every feature from the start. The ideal candidate is a full-stack data scientist with strong engineering instincts and clear data storytelling skills.
Description
You will be the face of the metrics team for cross-functional partners, owning KPIs end to end from definitions and instrumentation to reporting. You will build a strong understanding of our on-device telemetry, engineering workflows, CI/CD practices, and data systems, and use that context to create clear, reliable metrics. You will work closely with engineering, data science, and leadership to drive alignment and decisions.
Minimum Qualifications
BS/MS in Computer Science, Data Engineering, or equivalent experience and 6+ years experience applying data science techniques to real business problems.
Strong ability to turn ambiguous product or business questions into clear data solutions.
Strong programming and data skills, including SQL and Python, and experience with large-scale data pipelines.
Experience defining KPIs that reflect real product health.
Experience with data quality, validation, and large datasets.
Strong communication skills and comfort working across teams.
Preferred Qualifications
Experience with telemetry, observability, and measuring reliability or performance.
Ability to partner with engineers to diagnose and root cause data issues through understanding instrumentation and system behavior
Experience influencing engineering or product decisions using data.
Familiarity with distributed systems, modern analytics stacks, and privacy-aware measurement.
Sprachkenntnisse
- English
Hinweis für Nutzer
Dieses Stellenangebot stammt von einer Partnerplattform von TieTalent. Klicken Sie auf „Jetzt Bewerben“, um Ihre Bewerbung direkt auf deren Website einzureichen.