Data Scientist, AIML Data Scientist

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $172,100–$258,600 / yr
Posted: 102 days ago
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $160k

This role $215k

$83k most similar roles pay here $277k

This role pays more than 88% of similar roles. Most pay $126,800–$192,375 — the shaded band above. At the midpoint, this role pays about $215k versus about $160k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1785 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1446 roles with salary data.

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At a glance

TL;DR · Data Scientist, AIML Data Scientist

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As a Senior Data Scientist in Apple’s AIML Data Operations group, you will lead analysis into annotation project trends to uncover patterns in annotator performance, task complexity, and data characteristics, optimizing task design for efficiency and quality. Your day-to-day involves collaborating with cross-functional teams to run A/B experiments, develop capacity forecasts, and enhance automation strategies. You will leverage SQL, Python, or R to build machine learning models and sophisticated analytic solutions, ensuring high-quality annotated data supports unreleased products and groundbreaking AI technology. This role requires a deep understanding of analytics and experimentation, as well as the ability to communicate key insights effectively across various levels of the organization, driving performance improvements at a global scale.

Skills

Python R SQL Kafka Hadoop Spark PostgreSQL AWS Azure GCP CI/CD Git Jupyter Tableau PowerBI Docker Kubernetes Terraform Scikit-learn

What you'll do

Analyze trends to identify patterns in annotator performance and task complexity.
Evaluate tasks and data types for automation potential and optimize accordingly.
Translate insights into optimized project structures ensuring efficiency and quality.
Design, run, and analyze A/B experiments to establish best practices.
Contribute to capacity forecasting by converting quantitative analysis into forecasts.
Identify key factors improving productivity and quality in annotation projects.
Develop a holistic view of analyst behaviors to drive positive experiences.

What we're looking for

4+ years of experience in data science with proven analytical skills.
Mastery in SQL-based languages and proficiency in Python or R.
Strong hands-on experience with machine learning models and big data technologies.
Ability to develop meaningful analytic objectives from general business goals.
Experience in scalable schema designs, ETL processes, and query optimization.
Preferred: Master’s degree or PhD in a quantitative field.
Preferred: Experience deploying Large Language Models for operational efficiency.

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